Takahashi Sho
Faculty of Engineering Civil Engineering Advanced Social System | Associate Professor |
Education and Research Center for Mathematical and Data Science | Associate Professor |
■Researcher basic information
Profile Information
【学歴】
平成18年3月 木更津工業高等専門学校情報工学科 卒業.
平成20年3月 北海道大学工学部情報工学科 卒業.
平成22年3月 北海道大学大学院情報科学研究科メディアネットワーク専攻 修士課程 修了.
平成25年3月 北海道大学大学院情報科学研究科メディアネットワーク専攻 博士課程 修了.
【職歴】
平成22年4月 北海学園大学 工学部 非常勤講師.
平成23年4月 日本学術振興会 特別研究員.
平成25年4月 北海道大学大学院情報科学研究科 特任助教.
平成29年7月 北海道大学数理・データサイエンス教育研究センター 特任准教授.
平成30年4月 北海道大学大学院工学研究院 准教授.
平成30年9月-平成31年3月 フィレンツェ大学 客員教授.
【所属学会】
IEEE,電子情報通信学会,映像情報メディア学会,土木学会,自動車技術会,交通工学研究会,日本環境共生学会 各会員.博士(情報科学).
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Research Keyword
Research Field
Educational Organization
- Bachelor's degree program, School of Engineering
- Master's degree program, Graduate School of Engineering
- Doctoral (PhD) degree program, Graduate School of Engineering
■Career
Career
- Apr. 2018 - Present
Hokkaido University, Faculty of Engineering, Associate Professor - Sep. 2018 - Mar. 2019
University of Florence, Media Integration and Communication Center, Visiting Professor - Jul. 2017 - Mar. 2018
Hokkaido University, Education and Research Center for Mathematical and Data Science, Specially Appointed Associate Professor - Apr. 2013 - Jun. 2017
Hokkaido Univeristy, Graduate School of Information Science and Technology, (Specially Appointed) Assistant Professor - Apr. 2011 - Mar. 2013
The Japan Society for the Promotion of Science, JSPS Research Fellow - Apr. 2010 - Mar. 2012
Hokkai-Gakuen University, Faculty of Engineering, Part-time Lecturer
Educational Background
- Apr. 2010 - Mar. 2013, Hokkaido University, Graduate School of Information Science and Technology, Division of Media and Network Technologies, Japan
- Apr. 2008 - Mar. 2010, Hokkaido University, Graduate School of Information Science and Technology, Division of Media and Network Technologies, Japan
- Apr. 2006 - Mar. 2008, Hokkaido University, School of Engineering, Department of Information Engineering, Japan
- Apr. 2001 - Mar. 2006, Kisarazu National College of Technology, Department of Information and Computer Engineering, Japan
Committee Memberships
- Oct. 2023 - Present
北海道開発局 札幌開発建設部 一般国道5号創成川通 防災計画・施設検討会, 委員, Government - Jun. 2023 - Present
北海道開発局 札幌開発建設部 国道12号白石本通第二電線共同溝PFI事業 有識者等委員会, 委員, Government - Sep. 2022 - Present
北海道開発局 札幌開発建設部 創成トンネル浸水対策等技術検討会, 委員, Government - Sep. 2020 - Present
地域道路経済戦略研究会 北海道地方研究会, 委員, Government - Jun. 2020 - Present
北海道大規模小売店舗立地審議会, 特別委員, Autonomy - Apr. 2020 - Present
北海道開発局 稚内開発建設部 総合審査評価委員会, 委員, Government - Jun. 2019 - Present
北海道土木技術会道路研究会, 委員兼幹事, Others - Nov. 2020 - Mar. 2023
北海道積雪寒冷対応システム検討会, 座長, Autonomy - Apr. 2022 - Feb. 2023
交通工学研究会 第4回JSTEシンポジウム運営小委員会, 幹事, Society - Jul. 2022 - Oct. 2022
IEEE Global Conference on Consumer Electronics (GCCE 2022), Technical Program Committee Chair, Society - Jan. 2021 - Dec. 2021
IEEE Global Conference on Consumer Electronics (GCCE 2021), Conference Chair, Society - Apr. 2019 - Mar. 2021
土木学会北海道支部, 論文担当幹事・チーフ幹事, Society - Apr. 2020 - Feb. 2021
交通工学研究会 第2回JSTEシンポジウム運営小委員会, 幹事, Society - Jan. 2020 - Jan. 2021
International Conference on Pattern Recognition (ICPR 2020), Associate Editor, Society - Jan. 2019 - Dec. 2019
日本環境共生学会 第22回(2019年度)学術大会, 実行委員, Society
■Research activity information
Awards
- Jan. 2023, International Workshop on Advanced Image Technology 2023, Best Paper Award
Improvement of Nighttime Visibility Estimation Based on > Spatio-Temporal Correlation in Videos
Masahiro Yagi;Sho Takahashi;Toru Hagiwara - Dec. 2022, 土木学会, AI・データサイエンス論文賞
複数の車載センサーデータを統合した冬期の路面状態のLate Fusion > による推定モデル
石附将武;高橋翔;萩原亨;石井啓太;岩﨑悠志;森徹平;花塚泰史 - Oct. 2022, Japan Society of Transporation Engineers, Research Encouragement Award
歩行者の安心かつ円滑な横断を目的とした自動運転車による意思伝達装置に関する研究
Shunichi Wada;Sho Takahashi;Toru Hagiwara - 2021, 映像情報メディア学会, Tanba Takayanagi Paper Award
Multimodal Important Scene Detection in Far-view Soccer Videos Based on Single Deep Neural Architecture
Tomoki Haruyama;Sho Takahashi;Takahiro Ogawa;Miki Haseyama - Oct. 2020, 2020 IEEE 9th Global Conference on Consumer Electronics, IEEE GCCE 2020 Excellent Poster Award
An Estimation Method of Road Narrowing Condition in in-Vehicle Camera
Kozo Okumura, Sho Takahashi, Toru Hagiwara - Sep. 2020, IEEE International Conference on Consumer Electronics-Taiwan, Best Paper Award
An Estimation Method of Visibility Level on Winter Road Based on Multiple Features in CCTV Images
Shotaro Kawata;Sho Takahashi;Toru Hagiwara - Oct. 2019, IEEE 8th Global Conference on Consumer Electronics (GCCE), IEEE GCCE 2019 Excellent Poster Award
Masahiro Yagi;Sho Takahashi;Toru Hagiwara - Oct. 2019, IEEE 8th Global Conference on Consumer Electronics (GCCE), IEEE GCCE 2019 Excellent Student Paper Award
Takayuki Abe;Sho Takahashi;Toru Hagiwara - Oct. 2019, IEEE 8th Global Conference on Consumer Electronics (GCCE), IEEE GCCE 2019 Excellent Demo! Award, Gold Prize
Sho Takahashi;Masahiro Yagi;Toru Hagiwara - Oct. 2018, IEEE 7th Global Conference on Consumer Electronics (GCCE), 1st Prize IEEE GCCE 2018 Excellent Poster Award
Tomoki Haruyama;Sho Takahashi;Takahiro Ogawa;Miki Haseyama - Dec. 2017, Institute of Image Information and Television Engineers, Best Presentation Award
Sho Takahashi - Oct. 2013, IEEE 2nd Global Conference on Consumer Electronics, IEEE 2nd Global Conference on Consumer Electronics
高橋 翔 - Nov. 2009, 平成21年度電気・情報関係学会北海道支部連合大会, 優秀論文発表賞
高橋 翔
Papers
- AR-based Merging Assistance at Expressway and Its Verification
Sho Takahashi, Ryohei Maruyama, Toru Hagiwara
International Journal of Intelligent Transportation Systems Research, Dec. 2024
Scientific journal - Drivers' collision avoidance behavior: Timing of pedestrian detection when turning right at signalized intersections
Chinami Fukui, Sho Takahashi, Toru Hagiwara
Asian Transport Studies, 2024
Scientific journal - A Study on the Influence of Winter XRAIN Precipitation Intensity on Traffic Flow in Central Sapporo Based on Macroscopic Fundamental Diagram Theory
山城皓太郎, 萩原亨, 高橋翔
交通工学研究発表会論文集(Web), 43rd, 2023 - 複数の車載センサーデータを統合した冬期の路面状態のLate Fusionによる推定モデル
石附将武, 高橋翔, 萩原亨, 石井啓太, 岩﨑悠志, 森徹平, 花塚泰史
AI・データサイエンス論文集, Nov. 2022, [Peer-reviewed], [Corresponding author]
Japanese, Scientific journal - 予測誤差補正によるLSTMを用いた歩行軌跡予測の高精度化に関する研究
鴨藤功武, 高橋翔, 萩原亨
AI・データサイエンス論文集, Nov. 2022, [Peer-reviewed], [Corresponding author]
Japanese, Scientific journal - 複数識別器の確信度に基づくLate-fusionによる車載カメラ映像を用いた夜間の視界レベル推定
佐藤諒, 高橋翔, 萩原亨, 永田泰浩, 大橋一仁
AI・データサイエンス論文集, Nov. 2022, [Peer-reviewed], [Corresponding author]
Japanese, Scientific journal - Development of Road Visibility Inspection System Using Driving Video Images Recorded by On-board Video Camera
Kazuhito OHASHI, Yasuhiro NAGATA, Yasuhiro KANEDA, Toru HAGIWARA, Sho TAKAHASHI, Yuki NAKAMURA
ROUTES/ROADS Magazine, RR393-028, Jun. 2022, [Peer-reviewed]
English, Scientific journal - 空間周波数および深層学習に基づく機械学習による視程レベル推定 -特徴選択手法による空間周波数の選択効果-
高橋翔, 河田祥太朗, 萩原亨
土木学会論文誌 D3(土木計画学), 77, 5, I_1077, I_1084, May 2022, [Peer-reviewed], [Lead author]
Japanese, Scientific journal - Development of Poor Visibility Assessment Method in Winter Using Images Taken by On-Board Video Camera
Yuki Nakamura, Toru Hagiwara, Yasuhiro Nagata, Sho Takahashi
Journal of EASTS, 18, 1824, 1841, Mar. 2022, [Peer-reviewed], [Last author]
English, Scientific journal - Effects of Time-Gap Settings of Adaptive Cruise Control (ACC) on Driver’s Risk Feeling Estimated by the Car-Following Situation
Shuhei Wada, Sho Takahashi, Tomonori Ohiro, Kazunori Munehiro, Minoru Okada, Toru Hagiwara
Journal of EASTS, 14, 2133, 2148, Mar. 2022, [Peer-reviewed]
English, Scientific journal - Awareness of the prevention through design (PtD) concept among design engineers in the Philippines
Rimmon Labadan, Kriengsak Panuwatwanich, Sho Takahashi
Engineering Management in Production and Services, 14, 1, 78, 92, Walter de Gruyter GmbH, 01 Mar. 2022, [Peer-reviewed]
English, Scientific journal, Abstract
The “Prevention through Design” (PtD) concept considers construction safety during the design process. Several countries are currently practising PtD, including the UK, Singapore, Malaysia, Australia, and the USA, which is still not the case in the Philippines. The study presented in this paper aimed to indicate the current level of awareness of the PtD concept among the structural engineers and purposed to generate a basis of initiatives to introduce or improve the understanding and adoption of PtD in the Philippines. A knowledge, attitude, and practice (KAP) questionnaire was distributed to survey respondents selected through a snowball sampling method, consisting of structural engineers currently working in the Philippines. Sixty-one (61) structural engineers responded and were analysed in this study. Results indicated that PtD was relatively a new concept for most structural engineers in the Philippines. Similarly, the designers’ knowledge of the concept was still low. However, structural engineers viewed PtD as necessary and its implementation as essential in the construction industry. Despite the known concerns in the PtD implementation, structural engineers favoured the adoption of the concept. The paper also discussed challenges and key drivers for implementing PtD in the Philippines based on the questionnaire results and supporting literature reviews. The findings and methodology presented in this paper could serve as a baseline for a larger sample size covering other design trades, such as architectural, electrical, and mechanical design services leading to the broader adoption of PtD in the Philippines. Furthermore, the framework of this study could also apply to other countries with similar contexts. - 高速道路合流部の交通円滑化を支援する速度誘導灯に関する研究
大石侑亮, 河合レナ, 高橋翔, 萩原亨
交通工学論文集, 8, 2, A_54, A_61, Feb. 2022, [Peer-reviewed]
Japanese, Scientific journal - A Study on Pedestrian Recognition of Right-turn Drivers at Urban Intersections by using Virtual Reality Driving Simulator
Taisei Okazaki, Sho Takahashi, Ryohei Maruyama, Toru Hagiwara
交通工学論文集, 8, 2, A_185, A_193, Feb. 2022, [Peer-reviewed]
Japanese, Scientific journal - Image and CAIS Features-Based Estimation of Road Surface Condition on Winter Local Road.
Masamu Ishizuki, Sho Takahashi, Toru Hagiwara, Keita Ishii, Yuji Iwasaki, Teppei Mori, Yasushi Hanatsuka
11th IEEE Global Conference on Consumer Electronics(GCCE), 79, 80, IEEE, 2022
International conference proceedings - A Virtual Reality Driving Simulator with Gaze Tracking for Analyzing Driver's Behavior.
Ryohei Maruyama, Sho Takahashi, Toru Hagiwara
LifeTech, 144, 145, 2022, [Peer-reviewed]
English, International conference proceedings - An Estimation Method of Visibility Level Based on Multiple Models Using In-vehicle Camera Videos under Nighttime.
Ryo Sato, Masahiro Yagi, Sho Takahashi, Toru Hagiwara, Yasuhiro Nagata, Kazuhito Ohashi
GCCE, 530, 531, 2021, [Peer-reviewed]
International conference proceedings - Vehicle Behavior Measurement based-on RTK-GNSS for Driver's Risk Feeling Estimation.
Sho Takahashi, Shuhei Wada, Toru Hagiwara, Kazunori Munehiro
GCCE, 528, 529, 2021, [Peer-reviewed], [Lead author]
International conference proceedings - LSTM-Based Prediction Method of Crowd Behavior for Robust to Pedestrian Detection Error.
Isamu Kamoto, Takayuki Abe, Sho Takahashi, Toru Hagiwara
GCCE, 218, 219, 2021, [Peer-reviewed]
International conference proceedings - An Estimation Method of Road Surface Condition on Winter Expressway via Mobile Nets using In-vehicle Camera Images.
Tomoyuki Takase, Sho Takahashi, Toru Hagiwara, Tomonori Ohiro, Yuji Iwasaki, Teppei Mori, Yasushi Hanatsuka
GCCE, 109, 110, 2021, [Peer-reviewed]
International conference proceedings - An Edge Computing System for Estimating Road Surface Condition on Winter Expressway.
Masahiro Yagi, Tomoyuki Takase, Sho Takahashi, Toru Hagiwara, Tomonori Ohiro, Yuji Iwasaki, Teppei Mori, Yasushi Hanatsuka
GCCE, 71, 72, 2021, [Peer-reviewed]
International conference proceedings - Advanced Road Visibility Inspection System for Winter Road Maintenance Using Microcomputer.
Sho Takahashi, Toru Hagiwara, Ryo Sato, Kazuhito Ohashi, Yasuhiro Nagata
GCCE, 28, 29, 2021, [Peer-reviewed]
International conference proceedings - Fundamental Study for Adaptation Requirements of ACC (Adaptive Cruise Control) to Winter Road Environment
和田脩平, 高橋翔, 白石直之, 宗広一徳, 岡田稔, 内藤利幸, 萩原亨
交通工学論文集(Web), 7, 2, A_289, A_297, Japan Society of Traffic Engineers, 2021, [Peer-reviewed]
Japanese,In the present study, objective is to reveal the driver's subjective risk perception when closing to a preceding vehicle in car-following situation under snowy or dry/wet road conditions. It was assumed that the driver uses the ACC to follow a preceding vehicle, and the preceding vehicle decelerated and approached. The results of the field experiment shown that the driver's subjective risk perception to the preceding vehicle was increased by ACC use. The models for estimating the driver's subjective risk perception to the preceding vehicle based on values of the 1/TTC and the 1/THW in the situation of preceding vehicle deceleration were delivered in each type of road conditions (Risk Feeling equation). From the Risk Feeling equation, the THW of the ACC, which corresponds to the conventional driving of the driver's subjective risk perception to the preceding vehicle, is shown in each road conditions. It was suggested that longer value of the THW is required to reduce driver's risk feeling when driving with ACC on snowy roads.
- A Study on Effect of Speed Adjustment Delineator on Driver's Risk Avoiding Behavior with the Merging Vehicle in the case of using Adaptive Cruise Control System
KAWAI Rena, HAGIWARA Toru, TAKAHASHI Sho, TERAKURA Yoshihiro, OISHI Yusuke
JSTE Journal of Traffic Engineering, 7, 2, A_316, A_325, Japan Society of Traffic Engineers, 2021, [Peer-reviewed]
Japanese, Scientific journal,This study proposed speed adjustment delineators embedded in the center of the travel lane as a preliminary speed adjustment device for drivers who is operating a semi-automated vehicle to reduce conflicts with the merging vehicles on the expressway. We conducted experiments using a driving simulator with 46 participants, and the results of driving records and subjective evaluations showed that the information provided about speed adjustment delineators affected the driver's avoidance behavior. The participants who were explained the intention of the speed adjustment delineators selected the appropriate speed adjustment to follow the instructions of the speed guide light at the upstream of the nose end in the merging section. This result led to merging behavior smoothly and reduced the subjective risk perceived by the drivers due to the merging vehicles. In addition, based on the acceleration and deceleration behavior of drivers when the speed guide lights were not turned on, the proper location of the speed adjustment delineators were revealed.
- AR-based HMI for supporting Merging Behavior at Expressway and Its Verification
Maruyama Ryohei, Takahashi Sho, Hagiwara Toru, Terakura Yoshihiro
The Transactions of Human Interface Society, 23, 1, 19, 28, Human Interface Society, 2021, [Peer-reviewed]
Japanese, Scientific journal, This study tries to support merging behavior by providing information about the behavior of the mainline vehicle as a next-generation Human-Machine Interface (HMI) based on Augmented Reality (AR). Also, in this paper, we verify the effectiveness of visual information on the driver using AR by analyzing the gaze. Specifically, this paper provides information on the timing in which the merging vehicle cannot merge by using AR to the driver. This information is generated based on the position and speed of the mainline vehicle. In this study, a Virtual Reality (VR) driving simulator that can measure the gaze was developed for experiments. By utilizing the VR driving simulator, driving experiments that provide various kinds of information including AR to the merging vehicle was performed. Also, by using the obtained data at the driving experiments, the driver's gazes are analyzed. In this gaze analysis, we verify the burden on the driver of checking the mainline is reduced by the information provision. Furthermore, the timing of the merging is measured to evaluate the safety and smoothness of the merging. The experimental results suggested that providing the unsuitable timing of merging by AR enables the driver to understand easily the condition of the mainline. - EFFECTS OF WINTER ROAD SURFACE ON DRIVER’S RISK AVOIDANCE BEHAVIOR WHEN THE VEHICLE ARE ENTERING A CURVE WITH ADAPTIVE CRUISE CONTROL
白石直之, 高橋翔, 萩原亨, 岡田稔, 内藤利幸, 宗広一徳
土木学会論文集 D3(土木計画学)(Web), 76, 5, I_1409, I_1416, Japan Society of Civil Engineers, 2021, [Peer-reviewed]
Japanese,In winter, to drive a vehicle has a lot of difficulties due to road slipperiness, low visibility and narrowed road by lying snow. Understanding the driving environment where the driver feels danger is necessary to introduce SAE Level 2 or 3 in winter, so the present study aims to clarify driver's risk avoidance behavior when the drivers are using adaptive cruise control (ACC) under the winter road conditions. In an experiment on public road, a total 6 participants drove the test vehicle with ACC-ON conditions on the expressway and several local highways. We measured driver's risk avoidance behavior, and simultaneously measured road slipperiness, road geometry and weather condition. Results indicated that road slipperiness, road geometry and the vehicle speed have an effect on the occurring driver's risk avoidance behavior. Slippery road, hard geometry and high speed driving often lead the driver's risk avoidance behavior. According to this result, it is clarified that driver's risk avoidance behavior was reduced under low regulatory speed conditions on the expressway which the road geometry design was high level whereas the road surface conditions were slippery. It suggests that driver's risk avoidance behavior can reduce if the driving support system slows down before the vehicle approach such a slippery or hard geometry condition road.
- AVOIDANCE BEHAVIOR ON BICYCLE TRIPS DETECTION BASED ON MULTIMODAL APPROACH FOR ROAD MANAGEMENT
Masahiro Yagi, Sho Takahashi, Toru Hagiwara
Journal of JSCE D3(Infrastructure Planning and Management), 76, 5, I_899, I_907, 2021, [Peer-reviewed]
Scientific journal - EDGE COMPUTING SYSTEM FOR ACCUMULATING DATA OF AVOIDANCE BEHAVIOR ON BICYCLE TRIPS
Masahiro YAGI, Sho TAKAHASHI, Toru HAGIWARA
土木学会論文集 D3(土木計画学)(Web), 76, 5, I_859, I_867, Japan Society of Civil Engineers, 2021, [Peer-reviewed]
Japanese,Many road videos obtained by CCTV and dashcams are accumulated in organization of road administrators. However, since these data are simply accumulated as original video files, the data transmission via networks is very high cost and huge sized storage is required. Also, in the road situations where some obstacles such as damaged parts of roads and any unexpected objects exist, bicycles cannot travel normally and are forced to avoid them. Therefore, by realizing detection of the avoidance behavior on bicycle trips, more effective road management by road administrators can be expected. In this paper, we propose an edge computing system for accumulating the data of the avoidance behavior on bicycle trips while reducing the data size. This edge computing system contributes to realizing more effective and efficient road management.
- User-selectable event summarization in unedited raw soccer video via multimodal bidirectional LSTM
Tomoki Haruyama, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
ITE Transactions on Media Technology and Applications, 9, 1, 42, 53, 2021, [Peer-reviewed]
Scientific journal, A new method that generates user-selectable event summaries from unedited raw soccer videos is presented in this paper. Since there are more unedited raw soccer videos than broadcasted/distributed soccer videos and unedited videos have various viewers, it is necessary to analyze these videos for meeting the demands of various viewers. The proposed method introduces a multimodal CNN-BiLSTM architecture for analyzing unedited raw soccer videos. This architecture extracts candidate scenes for event summarization from unedited soccer videos and classifies these scenes into typical events. Finally, our method generates user-selectable event summaries by simultaneously considering the importance of candidate scenes and the event classification results. Experimental results using real unedited raw soccer videos show the effectiveness of our method. - Deterioration level estimation via neural network maximizing category-based ordinally supervised multi-view canonical correlation.
Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
Multim. Tools Appl., 80, 15, 23091, 23112, 2021, [Peer-reviewed]
Scientific journal, A deterioration level estimation method via neural network maximizing category-based ordinally supervised multi-view canonical correlation is presented in this paper. This paper focuses on real world data such as industrial applications and has two contributions. First, a novel neural network handling multi-modal features transforms original features into features effectively representing deterioration levels in transmission towers, which are one of the infrastructures, with consideration of only correlation maximization. It can be realized by setting projection matrices maximizing correlations between multiple features into weights of hidden layers. That is, since the proposed network has only a few hidden layers, it can be trained from a small amount of training data. Second, since there exist diverse characteristics and an ordinal scale in deterioration levels, the proposed method newly derives category-based ordinally supervised multi-view canonical correlation analysis (Co-sMVCCA). Co-sMVCCA enables estimation of effective projection considering both within-class divergence and the ordinal scale between classes. Experimental results showed that the proposed method realizes accurate deterioration level estimation. - A Study on Avoidance Behavior on Bicycle Trips Detection Using Multiple Features for Improvement Road Management
Masahiro Yagi, Sho Takahashi, Toru Hagiwara
2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020, 28 Sep. 2020, [Peer-reviewed]
International conference proceedings, This paper proposes a method for detecting avoidance behavior on bicycle trips in videos using multiple features. Our previous method detected the avoidance behavior on bicycle trips by using single feature based on rider's body parts. Also, the collaborative use of multiple features is effective for video analysis tasks. Thus, the proposed method introduces two new features for detection performance improvement. The introduced features are based on optical flow and Convolutional Neural Network (CNN), which are widely used in video analysis. Consequently, more accurate detection is realized. Experimental results show the effectiveness of the proposed method. - An Estimation Method of Candidate Region for Superimposing Information Based on Gaze Tracking Data in Soccer Videos
Genki Suzuki, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020, 28 Sep. 2020, [Peer-reviewed]
International conference proceedings, A novel method estimating candidate regions for superimposing information in soccer videos based on gaze tracking data is presented in this paper. The proposed method generates a likelihood map based on visual attention regions based on the gaze tracking data and detection results of objects such as players and soccer goals in soccer videos. Candidate regions for superimposing information are estimated by using the likelihood map. Experimental results show that the proposed method realizes effective candidate region estimation. - Automatic Generation of Training Data for Deep Learning in AR-based Transportation Support System
Takayuki Abe, Sho Takahashi, Toru Hagiwara
2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020, 28 Sep. 2020, [Peer-reviewed]
International conference proceedings, In this paper, we propose a method that automatically generates training data necessary for construction of deep learning-based model which supports indication of traffic data on augmented reality (AR). In the case of the data indication to road user by AR, there is a risk that important objects are hidden by the data. Thus, locations of the data indication should be adaptively determined. Therefore, accurate determination of the locations which recognizes the important objects via deep learning is expected. However, for deep learning, a large amounts of training data need to be prepared. In our method, the large amount of training data is automatically generated. Therefore, supporting location determination of the data indication via deep learning is realized. Experimental results show the effectiveness of our method. - An Estimation Method of Visibility Level on Winter Road Based on Multiple Features in CCTV Images
Shotaro Kawata, Sho Takahashi, Toru Hagiwara
2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020, 28 Sep. 2020, [Peer-reviewed]
International conference proceedings, Since drivers acquire a lot of information with eyes, the estimation of the level of visibility (visibility level) on the winter roads contributes toward enhancing traffic safety. Therefore, this paper proposes a method for estimating the visibility level on the winter roads from closed-circuit television (CCTV) images. In the proposed method, the visibility level of each image is estimated based on features acquired via Fourier transform and Convolutional Neural Network (CNN). Specifically, by constructing support vector machines (SVMs) for each feature, the probabilities of the visibility level are calculated. Furthermore, based on a comparison of the calculated probabilities of SVMs, the proposed method estimates the visibility level accurately. Experimental results show the effectiveness of the proposed method. - An Estimation Method of Visibility Level Based on Low Rank Matrix Completion Using GPV Data.
Gen Ohkama, Sho Takahashi, Toru Hagiwara
IEEE International Conference on Consumer Electronics - Taiwan(ICCE-TW), 1, 2, IEEE, 2020
International conference proceedings - SIMILAR INSPECTION DATA RETRIEVAL FOR ROAD STRUCTURE INSPECTION BASED ON CANONICAL CORRELATION BETWEEN EYE TRACKING DATA AND INSPECTION RECORDS
前田圭介, 斉藤僚汰, 高橋翔, 小川貴弘, 長谷山美紀
土木学会論文集 F3(土木情報学)(Web), 76, 1, 74, 76, 2020, [Peer-reviewed] - Similar scene retrieval in soccer videos with weak annotations by multimodal use of bidirectional LSTM.
Tomoki Haruyama, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
The 2nd ACM International Conference on Multimedia in Asia, 27, 8, ACM, 2020, [Peer-reviewed]
International conference proceedings, This paper presents a novel method to retrieve similar scenes in soccer videos with weak annotations via multimodal use of bidirectional long short-term memory (BiLSTM). The significant increase in the number of different types of soccer videos with the development of technology brings valid assets for effective coaching, but it also increases the work of players and training staff. We tackle this problem with a nontraditional combination of pre-trained models for feature extraction and BiLSTMs for feature transformation. By using the pre-trained models, no training data is required for feature extraction. Then effective feature transformation for similarity calculation is performed by applying BiLSTM trained with weak annotations. This transformation allows for highly accurate capture of soccer video context from less annotation work. In this paper, we achieve an accurate retrieval of similar scenes by multimodal use of this BiLSTM-based transformer trainable with less human effort. The effectiveness of our method was verified by comparative experiments with state-of-the-art using actual soccer video dataset. - Feature Integration Via Geometrical Supervised Multi-View Multi-Label Canonical Correlation For Incomplete Label Assignment.
Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
Proceedings - International Conference on Image Processing, ICIP, 2020-October, 46, 50, IEEE, 2020, [Peer-reviewed]
International conference proceedings, This paper presents feature integration via geometrical supervised multi-view multi-label canonical correlation analysis (GSM2CCA) for incomplete label assignment. The problem of incomplete labels is frequently encountered in the multi-label classification problem where the training labels are obtained via crowd-sourcing. In such a situation, consideration of only the label correlation, which is the basic approach, is not suitable for improvement of representation ability of features. For dealing with the incomplete label assignment, GSM2CCA constructs effective feature embedding space providing the discriminant ability by introducing both the multi-label correlation and feature similarity of the original feature space into its objective function. Since novel integrated features with high discriminant ability can be calculated by our GSM2CCA, performance improvement of multi-label classification with the incomplete label assignment is realized. The main contribution of this paper is the realization of the effective feature integration via the adoption of the combination use of label similarity and locality preserving projection of heterogeneous features for solving the problem of the incomplete label assignment. The effectiveness of GSM2CCA by applying GSM2CCA-based feature integration to heterogeneous features calculated from various convolutional neural network models is verified via experimental results. - An Estimation Method of Road Narrowing Condition in In-vehicle Camera.
Kozo Okumura, Sho Takahashi, Toru Hagiwara
2020 IEEE 9th Global Conference on Consumer Electronics, GCCE 2020, 733, 734, IEEE, 2020, [Peer-reviewed]
International conference proceedings, This paper proposes an estimation method of road narrowing condition by piled snow in in-vehicle camera image. The winter roads are possibly narrowed with the piled snow and caused traffic congestion. To maintain the urban functions the data accumulation of piled snow is very useful for snow removal planning. Therefore, in this paper, a novel method for estimating the road narrowing condition from in in-vehicle camera image is proposed. The proposed method is composed by hierarchical two steps which identify roads which have enough road capacity with piled snow and narrow roads which cause traffic congestion. These steps are used the low level image features and the position of road structures. In order to verify the effectiveness of the proposed method, we conduct two experiments. Experimental results show the effectiveness of our method. - Visibility Level Estimation in Winter CCTV Images Based on Decision Level Fusion Using Logistic Regression.
Shotaro Kawata, Sho Takahashi, Toru Hagiwara
2020 IEEE 9th Global Conference on Consumer Electronics, GCCE 2020, 640, 641, IEEE, 2020, [Peer-reviewed]
International conference proceedings, This paper proposes a method for estimating the degree of visibility (visibility level) in winter closed-circuit television (CCTV) images by decision level fusion based on logistic regression (LR). The proposed method classifies on the basis of two support vector machines (SVMs) classifiers and fuses the classification results by utilizing LRbased late fusion. In the proposed method, the SVMs which tentatively estimate visibility are constructed based on each CCTV image feature that represents the contrast of images and neuron values of the neural network. Also, the proposed method evaluates the visibility based on LR model trained by using SVM outputs. The effectiveness of our method is verified from experiments by utilizing actual CCTV images. - An Estimation Method of Visibility Level Based on Low Rank Matrix Completion Using Positional Relationship of GPV Data.
Gen Ohkama, Sho Takahashi, Toru Hagiwara
2020 IEEE 9th Global Conference on Consumer Electronics, GCCE 2020, 638, 639, IEEE, 2020, [Peer-reviewed]
International conference proceedings, This paper proposes a method for estimating visibility level based on low rank matrix completion using the positional relationship of GPV data. On a snowy day, the driving tasks can be hard because visibility is poor. By providing visibility level to drivers and road manager, safer traffic will be realized. To estimate visibility, weather data, which are significantly related to visibility, are used in the proposed method. In the proposed method, Grid Point Value (GPV) data and visibility data including missing values on unobserved points are generated to matrix corresponding to the actual location. The missing values are estimated based on low rank matrix completion. The effectiveness of our method are shown by utilizing actual data. - [Papers] Multimodal Important Scene Detection in Far-view Soccer Videos Based on Single Deep Neural Architecture
Haruyama Tomoki, Takahashi Sho, Ogawa Takahiro, Haseyama Miki
ITE Transactions on Media Technology and Applications, 8, 2, 89, 99, The Institute of Image Information and Television Engineers, 2020, [Peer-reviewed]
English, Scientific journal,The details of the matches of soccer can be estimated from visual and audio sequences, and they correspond to the occurrence of important scenes. Therefore, the use of these sequences is suitable for important scene detection. In this paper, a new multimodal method for important scene detection from visual and audio sequences in far-view soccer videos based on a single deep neural architecture is presented. A unique point of our method is that multiple classifiers can be realized by a single deep neural architecture that includes a Convolutional Neural Network-based feature extractor and a Support Vector Machine-based classifier. This approach provides a solution to the problem of not being able to simultaneously optimize different multiple deep neural architectures from a small amount of training data. Then we monitor confidence measures output from this architecture for the multimodal data and enable their integration to obtain the final classification result.
- [Paper] A Method for Player Importance Prediction from Player Network Using Gaze Position Estimated by LSTM
Suzuki Genki, Takahashi Sho, Ogawa Takahiro, Haseyama Miki
ITE Transactions on Media Technology and Applications, 8, 3, 151, 160, The Institute of Image Information and Television Engineers, 2020, [Peer-reviewed]
English, Scientific journal,A novel method for player importance prediction from a player network using gaze positions estimated by Long Short-Term Memory (LSTM) in soccer videos is presented in this paper. By newly using an estimation model of gaze positions trained by gaze tracking data of experienced persons, it is expected that the importance of each player can be predicted. First, we generate a player network by utilizing the estimated gaze positions and first-arrival regions representing players' connections, e.g., passes between players. The gaze positions are estimated by LSTM that is newly trained from the gaze tracking data of experienced persons. Second, the proposed method predicts the importance of each player by applying the Hypertext Induced Topic Selection (HITS) algorithm to the constructed network. Consequently, prediction of the importance of each player based on soccer tactic knowledge of experienced persons can be realized without constantly obtaining gaze tracking data.
- Estimation of Interest Levels From Behavior Features via Tensor Completion Including Adaptive Similar User Selection
Keisuke Maeda, Tetsuya Kushima, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
IEEE Access, 8, 126109, 126118, Institute of Electrical and Electronics Engineers ({IEEE}), 2020, [Peer-reviewed]
Scientific journal, A method for estimating interest levels from behavior features via tensor completion including adaptive similar user selection is presented in this paper. The proposed method focuses on a tensor that is suitable for data containing multiple contexts and constructs a third-order tensor in which three modes are 'products', 'users' and 'user behaviors and interest levels' for these products. By complementing this tensor, unknown interest level estimation of a product for a target user becomes feasible. For further improving the estimation performance, the proposed method adaptively selects similar users for the target user by focusing on converged estimation errors between estimated interest levels and known interest levels in the tensor completion. Furthermore, the proposed method can adaptively estimate the unknown interest from the similar users. This is the main contribution of this paper. Therefore, the influence of users having different interests is reduced, and accurate interest level estimation can be realized. In order to verify the effectiveness of the proposed method, we show experimental results obtained by estimating interest levels of users holding books. - Retrieval of similar scenes based on multimodal distance metric learning in soccer videos
Tomoki Haruyama, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
MMSports 2019 - Proceedings of the 2nd International Workshop on Multimedia Content Analysis in Sports, co-located with MM 2019, 10, 15, ACM, 15 Oct. 2019, [Peer-reviewed]
International conference proceedings, © 2019 Association for Computing Machinery. This paper presents a new method for retrieval of similar scenes based on multimodal distance metric learning in far-view soccer videos that broadly capture soccer fields and are not edited. We extract visual features and audio features from soccer video clips, and we extract text features from text data corresponding to these soccer video clips. In addition, distance metric learning based on Laplacian Regularized Metric Learning is performed to calculate the distances for each kind of features. Finally, by determining the final rank by integrating these distances, we realize successful multimodal retrieval of similar scenes from query scenes of soccer video clips. Experimental results show the effectiveness of our retrieval method. - Neural Network Maximizing Ordinally Supervised Multi-View Canonical Correlation for Deterioration Level Estimation
Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
Proceedings - International Conference on Image Processing, ICIP, 2019-September, 919, 923, IEEE, Sep. 2019, [Peer-reviewed]
International conference proceedings, © 2019 IEEE. This paper presents a neural network maximizing ordinally supervised multi-view canonical correlation for deterioration level estimation. The contributions of this paper are twofold. First, in order to calculate features representing deterioration levels on transmission towers, which is one of the infrastructures, a novel neural network handling multi-modal features is constructed from a small amount of training data. Specifically, in our method, effective transformation to features with high discriminant ability without using many hidden layers is realized by setting projection matrices maximizing correlation between multiple features into hidden layer's weights. Second, since there exists ordinal scale in deterioration levels, the proposed method newly derives ordinally supervised multi-view canonical correlation analysis (OsMVCCA). OsMVCCA enables estimation of the effective projection considering not only label information but also their ordinal scales. Experimental results show that the proposed method realizes accurate deterioration level estimation. - Performance improvement of users' interest estimation using viewing behavior data obtained by sensors
長谷山 美紀, 小川 貴弘, 髙橋 翔, 原川 良介
画像ラボ, 30, 7, 8, 12, 日本工業出版, Jul. 2019
Japanese - Estimation of users' interest levels using tensor completion with SemiCCA
Tetsuya Kushima, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
2019 IEEE 1st Global Conference on Life Sciences and Technologies, LifeTech 2019, 239, 240, IEEE, Mar. 2019, [Peer-reviewed]
International conference proceedings, © 2019 IEEE. This paper presents a new method for estimation of users' interest levels using tensor completion with SemiCCA. The proposed method extracts new features maximizing correlation between features calculated from partially paired users' behavior and contents with semi-supervised canonical correlation analysis (SemiCCA). By this approach, we can successfully use the contents that users have not viewed for the interest level estimation. Moreover, our method utilizes the tensor completion to estimate unknown interest levels. Consequently, in the proposed method, accurate estimation of interest levels using SemiCCA and the tensor completion is realized. Experimental results are shown to verify the effectiveness of the proposed method by using actual data. - Multi-feature Fusion Based on Supervised Multi-view Multi-label Canonical Correlation Projection.
Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2019, Brighton, United Kingdom, May 12-17, 2019, 2019-May, 3936, 3940, IEEE, 2019, [Peer-reviewed]
International conference proceedings, This paper presents multi-feature fusion based on supervised multi-view multi-label canonical correlation projection (sM2CP). The proposed method applies sM2CP-based feature fusion to multiple features obtained from various convolutional neural networks (CNNs) whose characteristics are different. Since new fused features with high representation ability can be obtained, performance improvement of multi-label classification is realized. Specifically, in order to tackle the multi-label problem, sM2CP introduces a label similarity information of label vectors into the objective function of supervised multi-view canonical correlation analysis. Thus, sM2CP can deal with complex label information such as multi-label annotation. The main contribution of this paper is the realization of feature fusion of multiple CNN features for the multi-label problem by introducing multi-label similarity information into the canonical correlation analysis-based feature fusion approach. Experimental results show the effectiveness of sM2CP, which enables effective fusion of multiple CNN features. - Convolutional sparse coding-based deep random vector functional link network for distress classification of road structures.
Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
Comput. Aided Civ. Infrastructure Eng., 34, 8, 654, 676, 2019, [Peer-reviewed]
English, Scientific journal, This paper presents a convolutional sparse coding (CSC)-based deep random vector functional link network (CSDRN) for distress classification of road structures. The main contribution of this paper is the introduction of CSC into a feature extraction scheme in the distress classification. CSC can extract visual features representing characteristics of target images because it can successfully estimate optimal convolutional dictionary filters and sparse features as visual features by training from a small number of distress images. The optimal dictionaries trained from distress images have basic components of visual characteristics such as edge and line information of distress images. Furthermore, sparse feature maps estimated on the basis of the dictionaries represent both strength of the basic components and location information of regions having their components, and these maps can represent distress images. That is, sparse feature maps can extract key components from distress images that have diverse visual characteristics. Therefore, CSC-based feature extraction is effective for training from a limited number of distress images that have diverse visual characteristics. The construction of a novel neural network, CSDRN, by the use of a combination of CSC-based feature extraction and the DRN classifier, which can also be trained from a small dataset, is shown in this paper. Accurate distress classification is realized via the CSDRN. - Multimodal Retrieval of Similar Soccer Videos Based on Optimal Combination of Multiple Distance Measures.
Tomoki Haruyama, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
2019 IEEE 8th Global Conference on Consumer Electronics, GCCE 2019, 665, 666, IEEE, 2019, [Peer-reviewed]
International conference proceedings, This paper presents a new multimodal method for retrieval of similar soccer videos based on optimal combination of multiple distance measures. Our method first extracts three types of Convolutional Neural Network-based features focusing the players' actions, the audience's cheers and prompt reports. Then, by applying the optimal distance measure to each feature, we calculate the similarities between a query video and videos in a database. Finally, we realize accurate retrieval of similar soccer videos by integrating these similarities. Experiments on actual soccer videos demonstrate encouraging results. - A Calculation Method of Degree of Data Indication Regions in First-Person View Videos for Improvement Transportation.
Takayuki Abe, Sho Takahashi, Toru Hagiwara
2019 IEEE 8th Global Conference on Consumer Electronics, GCCE 2019, 558, 559, IEEE, 2019, [Peer-reviewed]
International conference proceedings, In this paper, we propose a calculation method of degree for detecting regions of various data indication in first-person view videos. In recent years, contents of augmented reality (AR) have been implemented due to advances in computer hardware and interface. By indicating the data on road user's view, intelligent transport systems (ITS) is enhanced. However, since the user's view includes a lot of visually important information which the user should perceive, for indicating the data on the user's view, it is necessary to detect regions that do not include the information. In our method, degree as criteria is obtained based on seam carving and saliency map model. By utilizing the degree, it is possible to adaptively detect the regions of the data indication from different viewpoints. Experimental results show the effectiveness of our method. - Similarity Calculation Based on Pass Regions in Soccer Videos.
Sho Takahashi, Marco Bertini, Alberto Del Bimbo, Miki Haseyama, Toru Hagiwara
2019 IEEE 8th Global Conference on Consumer Electronics, GCCE 2019, 515, 516, IEEE, 2019, [Peer-reviewed]
International conference proceedings, This paper discusses a similarity calculation between soccer scenes in soccer videos. In the soccer games, pass regions, which are parts of the soccer court that include some pass courses are very important elements of each tactic in various scenes. Therefore, by visualizing the pass regions on soccer court in soccer videos, many audiences can easily understand tactics and game situations. Also, since the visualized pass regions describe tactics of soccer games, tactically similar scenes include similar pass regions each other. Thus, the similarity of soccer scenes is obtained by utilizing estimated pass regions in soccer videos. In this paper, we discuss the similarity calculation for soccer scenes. Specifically, the similarity of soccer scenes is compared which are calculated from a Deep Neural Network(DNN)-based visual feature of visualized pass regions, a DNN-based visual feature of original soccer image and Active Net-based feature of estimated pass regions. - An Evaluation Method of Obstacle Avoidance Behavior on Bicycle Trip Using Rider's Gesture.
Masahiro Yagi, Sho Takahashi, Toru Hagiwara
2019 IEEE 8th Global Conference on Consumer Electronics, GCCE 2019, 513, 514, IEEE, 2019, [Peer-reviewed]
International conference proceedings, This paper proposes a method for evaluation of obstacle avoidance behavior on bicycle trips in videos using rider's gesture based on OpenPose. Since a bicycle is a vehicle which is ridden by rotating a wheel with load transfer of a rider, there is a high correlation between bicycle behavior and rider's gesture. Therefore, we evaluate the obstacle avoidance behavior based on rider's gesture. In the proposed method, features about rider's gesture are obtained by utilizing OpenPose. In addition, support vector machines (SVMs) are constructed based on the features. Our method detects the obstacle avoidance behavior and classifies that to a degree of danger. Experimental results show the effectiveness of our method. - Analysis of Various Web Data for Visualization of Travel Time and Accessibility.
Kozo Okumura, Sho Takahashi, Toru Hagiwara
2019 IEEE 8th Global Conference on Consumer Electronics, GCCE 2019, 439, 440, IEEE, 2019, [Peer-reviewed]
International conference proceedings, This paper proposes a method for the calculation of travel time and the visualization of accessibility based on multiple data sources. In an environment where transport data are not fully open, construction of novel transportation systems which are planned based on enough data is limited. Our method calculates travel time based on data of multiple sources, which are not fully corrected data and visualizes novel accessibility by defining a novel index based on the travel time. The index is calculated from variance and mean of the travel time. As a result, a visual comparison of the accessibility between each area is realized by utilizing the proposed method. Thus, integrating some transport data is expected to contribute to constructing the optimal transportation system. Experimental results show the effectiveness of our evaluation method. - Data Accumulation System of Obstacle Avoidance Behavior on Bicycle Trip for Transportation Engineering.
Sho Takahashi, Masahiro Yagi, Toru Hagiwara
2019 IEEE 8th Global Conference on Consumer Electronics, GCCE 2019, 311, 312, IEEE, 2019, [Peer-reviewed]
International conference proceedings, This paper proposes a data accumulation system of obstacle avoidance behavior on bicycle trips in videos using gesture based on deep learning-based features. In the field of transportation engineering, realization of image/video processing-based methods for analyzing of various situations in transportation scenes has been expected. Therefore, many videos taken by CCTV and dashcams are accumulated in various transportation organizations. However, since these accumulates only raw videos which are huge size, that transmission, accumulate device and analysis of accumulated videos are very high cost as social infrastructures. Therefore, this paper constructs a system for accumulating small-sized videos, extracted features and analyzed results of the transportation scene, which is the obstacle avoidance behavior on bicycle trips. This system is constructed on a small size computer which can be worked by using the battery in order to equip on various structures. Also, an algorithm for detecting obstacle avoidance behavior on bicycle trips in videos are realized by utilizing deep learning-based features and support vector machines. - Interest Level Estimation Based on Tensor Completion via Feature Integration for Partially Paired User's Behavior and Videos.
Tetsuya Kushima, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
IEEE Access, 7, 148576, 148585, 2019, [Peer-reviewed]
English, Scientific journal, A novel method for interest level estimation based on tensor completion via feature integration for partially paired users' behavior and videos is presented in this paper. The proposed method defines a novel canonical correlation analysis (CCA) framework that is suitable for interest level estimation, which is a hybrid version of semi-supervised CCA (SemiCCA) and supervised locality preserving CCA (SLPCCA) called semi-supervised locality preserving CCA (S2LPCCA). For partially paired users' behavior and videos in actual shops and on the Internet, new integrated features that maximize the correlation between partially paired samples by the principal component analysis (PCA)-mixed CCA framework are calculated. Then videos that users have not watched can be used for the estimation of users' interest levels. Furthermore, local structures of partially paired samples in the same class are preserved for accurate estimation of interest levels. Tensor completion, which can be applied to three contexts, videos, users and 'canonical features and interest levels,' is used for estimation of interest levels. Consequently, the proposed method realizes accurate estimation of users' interest levels based on S2LPCCA and the tensor completion from partially paired training features of users' behavior and videos. Experimental results obtained by applying the proposed method to actual data show the effectiveness of the proposed method. - Team Tactics Estimation in Soccer Videos Based on a Deep Extreme Learning Machine and Characteristics of the Tactics.
Genki Suzuki, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
IEEE Access, 7, 153238, 153248, 2019, [Peer-reviewed]
English, Scientific journal, A novel method for estimating team tactics in soccer videos based on a Deep Extreme Learning Machine (DELM) and unique characteristics of tactics is presented in this paper. The proposed method estimates the tactics of each team from players' formations and enables successful training from a limited amount of training data. Specifically, the estimation of tactics consists of two stages. First, by utilizing two DELMs corresponding to the two teams, the proposed method estimates the provisional tactics of each team. Second, the proposed method updates the team tactics based on unique characteristics of soccer tactics, the relationship between tactics of the two teams and information on ball possession. Consequently, since the proposed method estimates the team tactics that satisfy these characteristics, accurate estimation results can be obtained. In an experiment, the proposed method is applied to actual soccer videos to verify its effectiveness. - Estimation of Deterioration Levels of Transmission Towers via Deep Learning Maximizing Canonical Correlation Between Heterogeneous Features
Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
IEEE Journal of Selected Topics in Signal Processing, 12, 4, 633, 644, Institute of Electrical and Electronics Engineers (IEEE), Aug. 2018, [Peer-reviewed]
English, Scientific journal, This paper presents estimation of deterioration levels of transmission towers via deep learning maximizing the canonical correlation between heterogeneous features. In the proposed method, we newly construct a correlation-maximizing deep extreme learning machine (CMDELM) based on a local receptive field (LRF). For accurate deterioration level estimation, it is necessary to obtain semantic information that effectively represents deterioration levels. However, since the amount of training data for transmission towers is small, it is difficult to perform feature transformation by using many hidden layers such as general deep learning methods. In CMDELM-LRF, one hidden layer, which maximizes the canonical correlation between visual features and text features obtained from inspection text data, is newly inserted. Specifically, by using projections obtained by maximizing the canonical correlation as weight parameters of the hidden layer, feature transformation for extracting semantic information is realized without designing many hidden layers. This is the main contribution of this paper. Consequently, CMDELM-LRF realizes accurate deterioration level estimation from a small amount of training data. - Distress classification of class-imbalanced inspection data via correlation-maximizing weighted extreme learning machine
Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
Advanced Engineering Informatics, 37, 79, 87, Elsevier Ltd, 01 Aug. 2018, [Peer-reviewed]
English, Scientific journal, This paper presents distress classification of class-imbalanced inspection data via correlation-maximizing weighted extreme learning machine (CMWELM). For distress classification, it is necessary to extract semantic features that can effectively distinguish multiple kinds of distress from a small amount of class-imbalanced data. In recent machine learning techniques such as general deep learning methods, since effective feature transformation from visual features to semantic features can be realized by using multiple hidden layers, a large amount of training data are required. However, since the amount of training data of civil structures becomes small, it becomes difficult to perform successful transformation by using these multiple hidden layers. On the other hand, CMWELM consists of two hidden layers. The first hidden layer performs feature transformation, which can directly extract the semantic features from visual features, and the second hidden layer performs classification with solving the class-imbalanced problem. Specifically, in the first hidden layer, the feature transformation is realized by using projections obtained by maximizing the canonical correlation between visual and text features as weight parameters of the hidden layer without designing multiple hidden layers. Furthermore, the second hidden layer enables successful training of our classifier by using weighting factors concerning the class-imbalanced problem. Consequently, CMWELM realizes accurate distress classification from a small amount of class-imbalanced data. - Automatic estimation of deterioration level on transmission towers via deep extreme learning machine based on local receptive field
Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
Proceedings - International Conference on Image Processing, ICIP, 2017-, ICIP, 2379, 2383, IEEE Computer Society, 20 Feb. 2018, [Peer-reviewed]
English, International conference proceedings, This paper presents an automatic estimation method of deterioration levels on transmission towers via Deep Extreme Learning Machine based on Local Receptive Field (DELM-LRF). Although Convolutional Neural Network (CNN) requires a large number of training images, it is difficult to prepare a sufficient number of training images of transmission towers. Thus, we generate a novel estimation method which enables training from a small number of training images. Specifically, we automatically extract image features based on Local Receptive Field (LRF) which combines convolution and pooling without using hand-craft features and estimate deterioration levels via Deep Extreme Learning Machine (DELM), which is a part of efficient deep learning methods. The derivation of DELM-LRF is the biggest contribution of this paper, and it can be trained from less training images compared to CNN. Experimental results show the effectiveness of DELM-LRF for the estimation of deterioration levels on transmission towers. Consequently, the proposed method makes it possible to approach challenging tasks with high expertise having difficulty in preparing enough images. - Estimation of Important Scenes in Soccer Videos Based on Collaborative Use of Audio-Visual CNN Features.
Tomoki Haruyama, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
IEEE 7th Global Conference on Consumer Electronics, GCCE 2018, Nara, Japan, October 9-12, 2018, 710, 711, IEEE, 2018, [Peer-reviewed]
International conference proceedings, This paper presents a novel method for estimating important scenes in soccer videos based on collaborative use of audio-visual Convolutional Neural Network (CNN) features. In soccer games, since game situations influence not only players' movements but also audiences' cheers, analyses of their audio and visual sequences are useful for the estimation of important scenes. In our method, such scenes are estimated from audio and visual CNN features via support vector machine (SVM) in each feature. Furthermore, by applying weighted majority voting based on confidences defined from the SVM-based estimation results, accurate estimation of important scenes becomes feasible. Experimental results show the effectiveness of our method. - Team Tactics Estimation in Soccer Videos via Deep Extreme Learning Machine Based on Players Formation.
Genki Suzuki, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
IEEE 7th Global Conference on Consumer Electronics, GCCE 2018, Nara, Japan, October 9-12, 2018, 116, 117, IEEE, 2018, [Peer-reviewed]
International conference proceedings, A method of team tactics estimation in soccer videos is presented in this paper. Our method enables estimation of basic tactics in each team on the basis of the Deep-Extreme Learning Machine (DELM) by using features of players formation. In the soccer games, team tactics relate to each other team. Therefore, the proposed method obtains final estimation results by utilizing two DELMs of each team and their relationship. Since the proposed method takes into consideration the relevance of the estimated tactics in each team, we realize accurate tactics estibimation. Experimental results using actual soccer videos showed the effectiveness of our method. - Binary Sparse Representation Based on Arbitrary Quality Metrics and Its Applications
OGAWA Takahiro, TAKAHASHI Sho, WADA Naofumi, TANAKA Akira, HASEYAMA Miki
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, 101, 11, 1776, 1785, 電子情報通信学会, 2018, [Peer-reviewed]
English, Scientific journal, <p>Binary sparse representation based on arbitrary quality metrics and its applications are presented in this paper. The novelties of the proposed method are twofold. First, the proposed method newly derives sparse representation for which representation coefficients are binary values, and this enables selection of arbitrary image quality metrics. This new sparse representation can generate quality metric-independent subspaces with simplification of the calculation procedures. Second, visual saliency is used in the proposed method for pooling the quality values obtained for all of the parts within target images. This approach enables visually pleasant approximation of the target images more successfully. By introducing the above two novel approaches, successful image approximation considering human perception becomes feasible. Since the proposed method can provide lower-dimensional subspaces that are obtained by better image quality metrics, realization of several image reconstruction tasks can be expected. Experimental results showed high performance of the proposed method in terms of two image reconstruction tasks, image inpainting and super-resolution.</p> - Interest Level Estimation of Items via Matrix Completion Based on Adaptive User Matrix Construction.
Tetsuya Kushima, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
2018 IEEE International Conference on Multimedia and Expo, ICME 2018, San Diego, CA, USA, July 23-27, 2018, 2018-July, 1, 6, IEEE Computer Society, 2018, [Peer-reviewed]
International conference proceedings, This paper presents a novel method for interest level estimation of items via matrix completion based on adaptive user matrix construction. The proposed method introduces a new criterion for adaptively constructing a user matrix that consists of user behavior features and interest levels, which are evaluated by target users and similar users. In the estimation, the matrix completion via rank minimization using the truncated nuclear norm is applied to the constructed matrix. The proposed method enables both of the interest level estimation of the target users and the selection of the similar users suitable for the estimation by monitoring errors caused in the matrix completion algorithm. The caused errors indicate the minimum differences between the estimated interest levels and true ones, and they can be regarded as the criterion for both of the optimal estimation and the adaptive selection. Furthermore, the proposed method uses weight matrices for decreasing an influence of missing data on the estimation. Consequently, accurate estimation of the interest levels becomes feasible by using the adaptively constructed matrix. Experimental results obtained by applying the proposed method to users' behavior and interest data show the effectiveness of the proposed method. - A RETRIEVAL METHOD OF SIMILAR INSPECTION RECORDS BASED ON EXPERIENCED INSPECTORS' EVALUATION
SAITO Ryota, TAKAHASHI Sho, OGAWA Takahiro, HASEYAMA Miki
土木学会論文集 F3(土木情報学)(Web), 74, 1, 67, 77, IEEE, 2018, [Peer-reviewed]
Japanese, Scientific journal, This paper presents a retrieval method of similar inspection records in road structures based on metric learning using experienced inspectors' evaluation. Inspection records of road structures include images and text-based information such as category of distress, damaged parts and degree of damage. The proposed method calculates distances from query inspection records, and rank lists of retrieval results are obtained for each feature. In this approach, the distance quantification are updated on the basis of experienced inspectors' evaluation. Finally, the proposed method obtains retrieval results by integrating the multiple rank lists. The experimental results show the effectiveness of the proposed method. - Interest level estimation based on matrix completion via rank minimization
Tetsuya Kushima, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
2017 IEEE 6th Global Conference on Consumer Electronics, GCCE 2017, 2017-, GCCE, 1, 2, Institute of Electrical and Electronics Engineers Inc., 19 Dec. 2017, [Peer-reviewed]
English, International conference proceedings, This paper presents a novel method for interest level estimation based on matrix completion via rank minimization. The proposed method estimates interest levels of target objects from human behavior features which are extracted during selecting these objects. Specifically, by adopting matrix completion via rank minimization, unknown interest levels can be estimated. Furthermore, the proposed method can also estimate unknown interest levels with some missing behavior features which are not correctly extracted by sensors. Experimental results show the effectiveness of the proposed method. - Distress Classification of Road Structures via Adaptive Bayesian Network Model Selection
K. Maeda, S. Takahashi, T. Ogawa, M. Haseyama
JOURNAL OF COMPUTING IN CIVIL ENGINEERING, 31, 5, ASCE-AMER SOC CIVIL ENGINEERS, Sep. 2017, [Peer-reviewed]
English, Scientific journal, This paper presents an accurate distress classification method via adaptive Bayesian network model selection for maintenance inspection of road structures. The main contribution of this paper is adaptive selection of two Bayesian network models concerning classification performance. The proposed method trains a tag-based Bayesian network model based on inspection items and estimates its classification performance. Furthermore, for distresses that degrade the classification performance of the tag-based Bayesian network model, the proposed method trains another multifeature Bayesian network model based on inspection items and distress images. Consequently, the proposed method can adaptively select optimal Bayesian network models according to the estimated performance of the tag-based Bayesian network model. In actual maintenance inspection, distresses are generally classified either from inspection items alone or from both inspection items and visual information of distress images-i.e., distress classification has two patterns. Therefore the adaptive model selection approach is suitable for this classification scheme. Experimental results show that the proposed method outperforms several comparative methods and is suitable for actual maintenance inspection due to its low computation costs. (C) 2017 American Society of Civil Engineers. - Biomimetics Image Retrieval Platform
Miki Haseyama, Takahiro Ogawa, Sho Takahashi, Shuhei Nomura, Masatsugu Shimomura
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, E100D, 8, 1563, 1573, IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG, Aug. 2017, [Peer-reviewed], [Invited]
English, Scientific journal, Biomimetics is a new research field that creates innovation through the collaboration of different existing research fields. However, the collaboration, i.e., the exchange of deep knowledge between different research fields, is difficult for several reasons such as differences in technical terms used in different fields. In order to overcome this problem, we have developed a new retrieval platform, "Biomimetics image retrieval platform," using a visualization-based image retrieval technique. A biological database contains a large volume of image data, and by taking advantage of these image data, we are able to overcome limitations of text-only information retrieval. By realizing such a retrieval platform that does not depend on technical terms, individual biological databases of various species can be integrated. This will allow not only the use of data for the study of various species by researchers in different biological fields but also access for a wide range of researchers in fields ranging from materials science, mechanical engineering and manufacturing. Therefore, our platform provides a new path bridging different fields and will contribute to the development of biomimetics since it can overcome the limitation of the traditional retrieval platform. - Deterioration Level Estimation on Transmission Towers via Extreme Learning Machine based on Combination Use of Local Receptive Field and Principal Component Analysis
K. Maeda, S. Takahashi, T. Ogawa, M. Haseyama
International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC), 457, 458, Jul. 2017, [Peer-reviewed]
English, International conference proceedings - Distress Classification of Class Imbalanced Data for Maintenance Inspection of Road Structures in Express Way
K. Maeda, S. Takahashi, T. Ogawa, M. Haseyama
International Conference on Civil and Building Engineering Informatics in conjunction with Conference on Computer Applications in Civil and Hydraulic Engineering (ICCBEI & CCACHE), 182, 185, Apr. 2017, [Peer-reviewed]
English, International conference proceedings - Distress classification of road structures via decision level fusion
Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
International Conference on Digital Signal Processing, DSP, 2016, DSP, 589, 593, Institute of Electrical and Electronics Engineers Inc., 01 Mar. 2017, [Peer-reviewed]
English, International conference proceedings, A distress classification method of road structures via decision level fusion is presented in this paper. In order to classify various kinds of distresses accurately, the proposed method integrates multiple classification results with considering their performance, and this is the biggest contribution of this paper. By introducing this approach, it becomes feasible to adaptively integrate the multiple classification results based on the accuracy of each classifier for a target sample. Consequently, realization of the accurate distress classification can be expected. Experimental results show that our method outperforms existing methods. - A method of important player extraction based on link analysis in soccer videos
Sho Takahashi, Miki Haseyama
ITE Transactions on Media Technology and Applications, 5, 2, 42, 48, Institute of Image Information and Television Engineers, 2017, [Peer-reviewed]
English, Scientific journal, In this paper, a method for extraction of important players in soccer videos based on link analysis is proposed. In a soccer match, players perform shoot tackles, assistance, and covering. Furthermore, the soccer tactics are defined the formation of players based on various relationships between players. The proposed method extracts the important players, in order to obtain information for understanding the soccer matches for various audiences. Specifically, our method notes that relationship between players, who cooperate with each other by the pass and the covering, is similar to relationship between web pages which are connected by links. First, the proposed method obtains player networks based on relationship between players in each team. The relationships are defined based on player positions and the possibility of the pass or the covering between players. Finally, in the proposed method, by applying the link analysis to the obtained player networks, important players are extracted. By realizing this approach, important players are extracted from the player networks based on the possibility of the pass or the covering between players. In the last of this paper, the above link analysis-based method was applied to actual soccer matches to show the reasonability of our method. - サッカー映像における試合内容の理解を促すデータの可視化
高橋 翔, 長谷山 美紀
映像情報メディア学会誌, 70, 5, 722, 724, Sep. 2016, [Peer-reviewed]
Japanese - A Note on Analysis of Gaze Data and Skill of Inspector in Embankment Inspection
高橋 翔, 三改木 裕矢, 小川 貴弘
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 115, 459, 177, 180, 電子情報通信学会, 22 Feb. 2016
Japanese - Decision Level Fusion-based Team Tactics Estimation in Soccer Videos
Genki Suzuki, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
2016 IEEE 5TH GLOBAL CONFERENCE ON CONSUMER ELECTRONICS, 1, 2, IEEE, 2016, [Peer-reviewed]
English, International conference proceedings, A decision-level fusion (DLF)-based team tactics estimation method in soccer videos is newly presented. In our method, tactics estimation based on audio-visual and formation features is newly adopted since the tactics of the soccer game are closely related to the audio-visual sequences and player positions. Therefore, by using these features, we classify the tactics via Support. Vector Machine (SVM). Furthermore, by applying DIA' to the SVM-based classification results, the two modalities are integrated to obtain more accurate tactics estimation results. Some results of experiments verify the superiority of our method. - Distress Classification of Road Structures via Multiple Classifier-based Bayesian Network
K. Maeda, S. Takahashi, T. Ogawa, M. Haseyama
International Workshop on Advanced Image Technology (IWAIT), 1, 4, 2016, [Peer-reviewed]
English, International conference proceedings - DLF-based speech segment detection and its application to audio noise removal for video conferences
Kazuto Sasaki, Takahiro Ogawa, Sho Takahashi, Miki Haseyama
ITE Transactions on Media Technology and Applications, 4, 1, 68, 77, Institute of Image Information and Television Engineers, 2016, [Peer-reviewed]
English, Scientific journal, A new decision-level fusion (DLF)-based speech segment detection method and its application to audio noise removal for video conferences are presented in this paper. The proposed method calculates visual and audio features from video sequences and audio signals, respectively, obtained in video conferences. Features extracted from mouth regions of participants and attribution degrees of speech class are used as visual and audio features, respectively, and Support Vector Machine (SVM)-based classification is performed by using each kind of feature. The SVM classifier performs two-class classification of speech and non-speech segments to realize speech segment detection. From the detection results obtained from the visual and audio features, DLF based on Supervised Learning from Multiple Experts is performed to successfully obtain the final detection results with focus on the accuracy of each detection result. Then, from audio signals in the non-speech segments detected by our method, we can extract noise information to realize accurate audio noise removal in the speech segments. - 6. Visualization Methods for Encourage Experience of Sports in Soccer Videos
Takahashi Sho, Haseyama Miki
The Journal of The Institute of Image Information and Television Engineers, 70, 9, 722, 724, The Institute of Image Information and Television Engineers, 2016
Japanese, Scientific journal - Improvement of video coding efficiency based on sparse contractive mapping approach
Zaixing He, Takahiro Ogawa, Sho Takahashi, Miki Haseyama, Xinyue Zhao
NEUROCOMPUTING, 173, 1898, 1907, ELSEVIER SCIENCE BV, Jan. 2016, [Peer-reviewed]
English, Scientific journal, This paper presents a new method for improving video coding efficiency based on a sparse contractive mapping approach. The proposed method introduces a new sparse contractive mapping approach to replace the traditional intra prediction in the video coding standards such as H.264/AVC. Specifically, the intra- and its following inter-frame are respectively approximated by the sparse representation, satisfying contractive mapping. Then these two frames can be reconstructed from an arbitraryinitial image by utilizing a few representation coefficients. With this advantage, the proposed method reduces the total amount of bits by removing MBs in the target I frame, whose approximation performance is higher than the others in the encoder. Furthermore, by transmitting the representation coefficients of the removed MBs, these MBs can be accurately reconstructed in the decoder. Since the reconstruction performance is better than that of the conventional approach, the proposed method can remove more MBs from the target video sequences, and reduction of total amount of bits can be feasible. Therefore, the proposed method realizes the improvement of the video coding efficiency. Some experimental results are shown to verify the superior performance of the proposed method to that of H.264/AVC. The results also demonstrate that the bit-saving performance of the proposed method is comparable to that of H.2651 HEVC. (C) 2015 Elsevier B.V. All rights reserved. - Player Tracking in Far-View Soccer Videos Based on Composite Energy Function
Kazuya Iwai, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, E97D, 7, 1885, 1892, IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG, Jul. 2014, [Peer-reviewed]
English, Scientific journal, In this paper, an accurate player tracking method in far-view soccer videos based on a composite energy function is presented. In far-view soccer videos, player tracking methods that perform processing based only on visual features cannot accurately track players since each player region becomes small, and video coding causes color bleeding between player regions and the soccer field. In order to solve this problem, the proposed method performs player tracking on the basis of the following three elements. First, we utilize visual features based on uniform colors and player shapes. Second, since soccer players play in such a way as to maintain a formation, which is a positional pattern of players, we use this characteristic for player tracking. Third, since the movement direction of each player tends to change smoothly in successive frames of soccer videos, we also focus on this characteristic. Then we adopt three energies: a potential energy based on visual features, an elastic energy based on formations and a movement direction-based energy. Finally, we define a composite energy function that consists of the above three energies and track players by minimizing this energy function. Consequently, the proposed method achieves accurate player tracking in far-view soccer videos. - A new method for error degree estimation in numerical weather prediction via MKDA-based ordinal regression
Takahiro Ogawa, Shintaro Takahashi, Sho Takahashi, Miki Haseyama
EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING, 2014, 1, 115, 115, SPRINGER INTERNATIONAL PUBLISHING AG, Jul. 2014, [Peer-reviewed]
English, Scientific journal, This paper presents a new method for estimating error degrees in numerical weather prediction via multiple kernel discriminant analysis (MKDA)-based ordinal regression. The proposed method tries to estimate how large prediction errors will occur in each area from known observed data. Therefore, ordinal regression based on KDA is used for estimating the prediction error degrees. Furthermore, the following points are introduced into the proposed approach. Since several meteorological elements are related to each other based on atmospheric movements, the proposed method merges such heterogeneous features in the target and neighboring areas based on a multiple kernel algorithm. This approach is based on the characteristics of actual meteorological data. Then, MKDA-based ordinal regression for estimating the prediction error degree of a target meteorological element in each area becomes feasible. Since the amount of training data obtained from known observed data becomes very large in the training stage of MKDA, the proposed method performs simple sampling of those training data to reduce the number of samples. We effectively use the remaining training data for determining the parameters of MKDA to realize successful estimation of the prediction error degree. - Bayesian Network-based Distress Estimation Using Image Features in Road Structure Assessment
Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
2014 IEEE 3RD GLOBAL CONFERENCE ON CONSUMER ELECTRONICS (GCCE), 169, 170, IEEE, 2014, [Peer-reviewed]
English, International conference proceedings, This paper presents a Bayesian network-based method for estimating a distress of road structures from inspection data. The distress is represented by a damage of road structures and its degree. In the previous work, the distress was estimated by utilizing Bayesian network based on categories of road structures, details of road structures and damaged parts. However, inspection data include not only the above items but also images of the distress. Therefore, by introducing the use of the images to the previous work, improvement of the distress estimation accuracy can be expected. The proposed method calculates Bayesian network from inspection items and their corresponding images to perform the distress estimation. Experimental results show the effectiveness of the proposed method. - Player Tracking by Using Level-Set Method in Soccer Video
TAKAHASHI Sho, LIM Wonkuk, HASEYAMA Miki
電子情報通信学会論文誌 D, 96, 3, 695, 703, Mar. 2013, [Peer-reviewed]
Japanese - ACTIVE GRID-BASED METHOD FOR VISUALIZING PASS REGIONS IN SOCCER VIDEOS
Sho Takahashi, Miki Haseyama
ELECTRONIC PROCEEDINGS OF THE 2013 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO WORKSHOPS (ICMEW), 1, 6, IEEE, 2013, [Peer-reviewed]
English, International conference proceedings, This paper presents a method for visualizing pass regions that have high probabilities of the pass succeeding from broadcast soccer videos. In soccer matches, players discover pass regions based on player position geometry and player velocities. Therefore, by using player position geometry and player velocities, which are obtained from a broadcast soccer video, we can visualize pass regions. The proposed method is realized by the following two steps. 1) Generation of new three-dimensional data (volume data) for analyzing pass regions, which are not visible. 2) Visualization of pass regions. In the first step, volume data are generated from player position geometry and player velocities. By generating the volume data, which express the player position geometry and the player velocities, analysis of invisible pass regions is enabled. In the second step, by applying Active grid to the generated volume data, pass regions are visualized. Specifically, lattice points of the Active grid converge to the pass regions. Therefore, positions of the pass regions on the pitch can be visualized from densities of the lattice points. In the experiment, the proposed method is applied to actual TV programs to verify its effectiveness. - Adaptive parameter setting for pass region estimation in soccer videos and its performance verification
Sho Takahashi, Miki Haseyama
2013 IEEE 2nd Global Conference on Consumer Electronics, GCCE 2013, 271, 272, IEEE, 2013, [Peer-reviewed]
English, International conference proceedings, This paper proposes an accurate pass region estimation method by introducing adaptive parameter settings. Our previous paper proposed a pass region estimation method by utilizing average values of ball and player velocities. However, such velocities vary according to player density and skill. Therefore, in order to realize a more accurate pass region estimation, the proposed method obtains parameters, which are ball and player velocities, from player positions in a target soccer video. By introducing the above parameter settings to pass region estimation, more realistic pass region can be obtained. Consequently, the accurate method of pass region estimation is realized. © 2013 IEEE. - Active Grid-based Pass Region Estimation from Multiple Frames of Broadcast Soccer Videos
Takahashi Sho, Haseyama Miki
ITE Transactions on Media Technology and Applications, 1, 3, 220, 225, The Institute of Image Information and Television Engineers, 2013, [Peer-reviewed]
English, Scientific journal, An Active grid-based method for estimating pass regions from broadcast soccer videos is presented in this paper. It is assumed that the pass region has a high probability of the pass succeeding. In soccer matches, players discover pass regions based on previous and current player positions. In conventional methods, pass regions are estimated by applying Active Net to only a single frame of a soccer video. In the proposed method, Active grid is applied to three-dimensional data by which frames of the soccer video are connected with the temporal dimension. The proposed method then realizes robust estimation of pass regions based on multiple frames of player positions. The proposed method was applied to actual TV programs to verify its effectiveness. - Active Net-Based Non-interception Region Estimation in Soccer Videos
TAKAHASHI Sho, KON Hirofumi, HASEYAMA Miki
The IEICE transactions on information and systems, 92, 4, 501, 510, The Institute of Electronics, Information and Communication Engineers, 01 Apr. 2009, [Peer-reviewed]
Japanese, Scientific journal, 本論文では,チームスポーツ映像からアクティブネットを用いてパス可能領域を推定する手法を提案する.チームスポーツ映像の一つであるサッカー映像の意味内容解析を行うために重要なサッカーの戦術は,選手の移動とボール運びによって表現されるため,ボール運びを実現するパスを分析することは重要である.一般にパスコースはボール保持者と味方チームの選手へとつながる緩やかな曲線で表される.提案手法では,新たなエネルギーの定義とパス可能領域を推定するための画像生成により,アクティブネットを用いて前述の曲線が存在する領域を抽出する.また,パス可能領域は守備の選手から離れるほど,パスが成功する可能性が高いという特徴をもつ.提案手法では,格子点の密度に着眼することで,パスが成功する可能性をパス可能領域の推定と同時に得る.更に,アクティブネットの収束結果は多少の選手位置の誤差を許容するため,選手の動きを用いた従来手法における,選手位置の誤差の影響を受けやすいという問題点を解決することが可能である.したがって,提案手法はカメラワークが存在し,高精度な選手位置の推定が困難であるテレビ映像に対しても,高精度にパス可能領域の推定が可能である.
Other Activities and Achievements
- 道路システムを支える画像モニタリングとデジタルツイン—特集 交通システムを支える技術
髙橋 翔, 光技術コンタクト = Optical and electro-optical engineering contact, 61, 10, 16, 23, Oct. 2023
光学工業技術協会, Japanese - 次世代情報化社会としてのマネジメントへのAI活用とデジタルツイン
髙橋 翔, Docon report / Docon report編集会 編, 213, 2, 7, Dec. 2022
ドーコン, Japanese - A Note on Position Estimation of Superimposing Information in Soccer Videos : Decision of Object Placement Based on User's Gaze Position and Players' Positions
鈴木 元樹, 高橋 翔, 小川 貴弘, 長谷山 美紀, 映像情報メディア学会技術報告 = ITE technical report, 45, 4, 77, 81, Feb. 2021
映像情報メディア学会, Japanese - Development of Speed Adjustment Delineator to Assist Smooth Merging on the Expressway
大石 侑亮, 河合 レナ, 高橋 翔, 萩原 亨, 交通工学研究発表会論文集, 41, 2, 325, 331, 2021, [Peer-reviewed]
交通工学研究会, Japanese - Drivers' Perception of Pedestrians Crossing the Street in Turn Right at Urban Intersection by Using Virtual Reality Driving Simulator
岡崎 泰勢, 高橋 翔, 丸山 凌平, 萩原 亨, 交通工学研究発表会論文集, 41, 363, 370, 2021
交通工学研究会, Japanese - Driver’s Risk Feeling in Car-following Situation Using Adaptive Cruise Control on Winter Road Conditions
川島省吾, 和田脩平, 高橋翔, 萩原亨, 自動車技術会大会学術講演会講演予稿集(Web), 2021, 2021 - Development of VR driving simulator for analysing driving behavior in right turn at intersections
岡崎泰勢, 萩原亨, 高橋翔, 丸山凌平, 土木学会北海道支部論文報告集(CD-ROM), 77, 2021 - A Validation of Pedestrian Tracking for Predicting Crowd Behavior in Fixed-point Camera Videos
鴨藤功武, 高橋翔, 萩原亨, 土木学会北海道支部論文報告集(CD-ROM), 77, 2021 - A Study on Evaluating the Impact of Automated Vehicles on Winter Traffic Using VISSIM
小島怜, 萩原亨, 高橋翔, 有村幹治, 和田脩平, 土木学会北海道支部論文報告集(CD-ROM), 77, 2021 - A Study on Estimating for Visibility Level at Nighttime via Machine Learning Using In-vehicle Camera Videos
佐藤諒, 高橋翔, 萩原亨, 永田泰浩, 大橋一仁, 土木学会北海道支部論文報告集(CD-ROM), 77, 2021 - VISIBILITY ESTIMATION VIA SPATIAL FREQUENCY AND DEEP LEARNING-BASED MACHINE LEARNING-AFFECTION OF FEATURE SELECTION IN SPATIAL FREQUENCY-BASED FEATURES-
高橋翔, 河田祥太朗, 萩原亨, 土木計画学研究・講演集(CD-ROM), 63, 2021 - DECISION OF ANALYSIS REGION FOR POOR VISIBILITY DETECTION CAUSED BY SNOWSTORM AT NIGHT IN CCTV CAMERA IMAGES
八木雅大, 高橋翔, 萩原亨, 土木計画学研究・講演集(CD-ROM), 63, 2021 - A Study on Hierarchical Estimation of Road Narrowing Conditions by Piled Snow in In-vehicle Cameras
奥村 耕三, 高橋 翔, 萩原 亨, 映像情報メディア学会技術報告 = ITE technical report, 44, 34, 1, 4, Dec. 2020
映像情報メディア学会, Japanese - A Study on Bicycle Behavior-based Edge Computing System for Supporting Road Management
八木 雅大, 高橋 翔, 萩原 亨, 映像情報メディア学会技術報告 = ITE technical report, 44, 34, 5, 8, Dec. 2020
映像情報メディア学会, Japanese - Presentation Region Calculation of Information Based on Gaze Tracking Data in Soccer Videos (ITS : Intelligent Transport Systems Technology)
鈴木 元樹, 高橋 翔, 小川 貴弘, 長谷山 美紀, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 119, 421, 91, 95, 27 Feb. 2020
電子情報通信学会, Japanese - A Note on Event Classification in Soccer Videos Using Bidirectional LSTM (ITS : Intelligent Transport Systems Technology)
春山 知生, 高橋 翔, 小川 貴弘, 長谷山 美紀, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 119, 421, 371, 375, 27 Feb. 2020
電子情報通信学会, Japanese - A Study on Identification of Winter Road Surface in Expressway via Machine Learning Using In-vehicle Camera Videos
高瀬 智之, 高橋 翔, 萩原 亨, 映像情報メディア学会技術報告 = ITE technical report, 44, 6, 31, 34, Feb. 2020
映像情報メディア学会, Japanese - サッカー映像視聴時の視線データを用いた情報の提示領域の算出に関する検討 (マルチメディアストレージ ヒューマンインフォメーション メディア工学 映像表現&コンピュータグラフィックス)
鈴木 元樹, 高橋 翔, 小川 貴弘, 長谷山 美紀, 映像情報メディア学会技術報告 = ITE technical report, 44, 6, 91, 95, Feb. 2020
映像情報メディア学会, Japanese - A Note on Event Classification in Soccer Videos Using Bidirectional LSTM
春山 知生, 高橋 翔, 小川 貴弘, 長谷山 美紀, 映像情報メディア学会技術報告 = ITE technical report, 44, 6, 371, 375, Feb. 2020
映像情報メディア学会, Japanese - EDGE COMPUTING SYSTEM FOR ACCUMULATING DATA OF AVOIDANCE BEHAVIOR ON BICYCLE TRIPS
八木雅大, 高橋翔, 萩原亨, 土木計画学研究・講演集(CD-ROM), 61, 2020 - 深層学習を用いたARによる道路情報提示のための学習データの自動生成に関する検討
阿部恭征, 高橋翔, 萩原亨, 土木学会北海道支部論文報告集(CD-ROM), 76, 2020 - Effects of Road Slipperiness and Road Geometry on Driver’s Risk Behavior When the Drivers Are Using Adaptive Cruise Control under the Winter Road Conditions
白石直之, 萩原亨, 高橋翔, 岡田稔, 内藤利幸, 宗広一徳, 自動車技術会大会学術講演会講演予稿集(CD-ROM), 2020, 2020 - Effects of Winter Road Surface on Driver’s Risk Avoidance Behavior when the Vehicle Are Entering a Curve with Adaptive Cruise Control
白石直之, 高橋翔, 萩原亨, 岡田稔, 内藤利幸, 宗広一徳, 土木計画学研究・講演集(CD-ROM), 61, 2020 - DRIVER’S RISK-AVOIDING BEHAVIOR WHEN THE DRIVER USES ADAPTIVE CRUISE CONTROL ON THE EXPRESSWAY IN WINTER
川島彰悟, 和田脩平, 大廣智則, 高橋翔, 萩原亨, 土木計画学研究・講演集(CD-ROM), 61, 2020 - Relationship Between Risk Avoidance Behavior and Running Conditions of Adaptive Cruise Control on Snowy Road
和田脩平, 高橋翔, 白石直之, 宗弘一徳, 岡田聡, 内藤利幸, 萩原亨, 交通工学研究発表会論文集(CD-ROM), 40th, 2020 - A note on interest level estimation for videos using users' behavior based on OpenPose
九島 哲哉, 高橋 翔, 小川 貴弘, 長谷山 美紀, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 118, 449, 351, 354, 19 Feb. 2019
電子情報通信学会, Japanese - A Method for Predicting Importance of Attack Players based on Gaze Tracking Data in Soccer Videos
鈴木 元樹, 高橋 翔, 小川 貴弘, 長谷山 美紀, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 118, 449, 355, 359, 19 Feb. 2019
電子情報通信学会, Japanese - A Note on Accurate Estimation of Deterioration Levels on Transmission Towers via Deep Learning Using Heterogeneous Features
前田 圭介, 高橋 翔, 小川 貴弘, 長谷山 美紀, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 118, 449, 361, 364, 19 Feb. 2019
電子情報通信学会, Japanese - A note on interest level estimation for videos using users' behavior based on OpenPose
九島 哲哉, 高橋 翔, 小川 貴弘, 長谷山 美紀, 映像情報メディア学会技術報告 = ITE technical report, 43, 5, 351, 354, Feb. 2019
映像情報メディア学会, Japanese - A Method for Predicting Importance of Attack Players based on Gaze Tracking Data in Soccer Videos
Genki Suzuki, Sho Takahashi, Takahiro Ogawa, Miki Haseyama, 2019 IEEE 8th Global Conference on Consumer Electronics, GCCE 2019, 43, 5, 355, 359, Feb. 2019
This paper presents a new method for predicting importance of attack players based on multiple gaze tracking data in soccer videos. In order to understand the game situation in the soccer game, experienced soccer players look at the movement, position, and space which are other players more often and faster than inexperienced players. Also, these features are different from each experienced player. For this reason, the gaze tracking data of experienced soccer player is useful for tactical analysis. Therefore, by introducing the gaze tracking data of multiple experienced soccer players into the importance prediction, more robust prediction than a method which use only one player's gaze data can be expected. Since this predicted importance is obtained from gaze data of the experienced soccer players, the obtained one is more useful data for understanding soccer game situation. Therefore, the proposed method can contribute to automatically data generation for developing novel services of video/data distribution that supports to easily understanding of video contents for many viewers. Experimental results using actual soccer videos showed the effectiveness of our method., IEEE, Japanese - A Note on Accurate Estimation of Deterioration Levels on Transmission Towers via Deep Learning Using Heterogeneous Features
前田 圭介, 高橋 翔, 小川 貴弘, 長谷山 美紀, 映像情報メディア学会技術報告 = ITE technical report, 43, 5, 361, 364, Feb. 2019
映像情報メディア学会, Japanese - サッカー映像視聴時の視線データを用いた周辺視に基づく攻撃選手の重要度算出に関する検討
鈴木元樹, 高橋翔, 小川貴弘, 長谷山美紀, 電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 2019, 2019 - 複数の特徴量から得られる類似度の統合に基づくサッカー映像における類似場面検索の高精度化に関する検討
春山知生, 高橋翔, 小川貴弘, 長谷山美紀, 電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 2019, 2019 - SUPERIORITY ANALYSIS OF CCS BASED ON COST OF MOVEMENTS IN URBAN AREA
笠原光将, 高橋翔, 萩原亨, 土木計画学研究・講演集(CD-ROM), 59, 2019 - A NOTE ON DETECTION OF AVOIDANCE BEHAVIOR ON BICYCLE TRIP USING OPENPOSE AND MULTIPLE-CLASSIFIERS
八木雅大, 高橋翔, 萩原亨, 土木計画学研究・講演集(CD-ROM), 60, 2019 - Field position estimation in soccer videos using convolutional neural network-based image features
Genki Suzuki, Sho Takahashi, Takahiro Ogawa, Miki Haseyama, Proceedings of SPIE - The International Society for Optical Engineering, 11049, 01 Jan. 2019
© COPYRIGHT SPIE. This paper presents a novel estimation method of field positions in soccer videos using Convolutional Neural Network (CNN)-based image features. CNN-based features have been well known to be ei€ective for tasks in machine learning. Therefore, the proposed method adopts CNN-based image features. By using these image features, the proposed method enables accurate estimation of soccer field positions than handcrafted features, i.e., Hough transform-based features. We show the ei€ectiveness of our method via experiment results using actual soccer videos. - Trial Introduction of Convolutional Sparse Coding for Accurate Distress Classification of Road Structures
前田 圭介, 高橋 翔, 小川 貴弘, 長谷山 美紀, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 117, 431, 189, 194, 15 Feb. 2018
電子情報通信学会, Japanese - A note on accurate retrieval of similar inspection records based on canonical correlation between eye tracking data and inspection records
斉藤 僚汰, 高橋 翔, 小川 貴弘, 長谷山 美紀, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 117, 432, 195, 200, 15 Feb. 2018
電子情報通信学会, Japanese - A Note on Recurrent Neural Network-based Tactics Estimation in Soccer Videos
鈴木 元樹, 高橋 翔, 小川 貴弘, 長谷山 美紀, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 117, 431, 131, 135, 15 Feb. 2018
電子情報通信学会, Japanese - A Study on Active Net-based Estimation of Pass Region in Rugby Videos
高橋 翔, 長谷山 美紀, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 117, 431, 137, 142, 15 Feb. 2018
電子情報通信学会, Japanese - Trial Introduction of Convolutional Sparse Coding for Accurate Distress Classification of Road Structures
前田 圭介, 高橋 翔, 小川 貴弘, 長谷山 美紀, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 117, 432, 189, 194, 15 Feb. 2018
電子情報通信学会, Japanese - A note on accurate retrieval of similar inspection records based on canonical correlation between eye tracking data and inspection records
斉藤 僚汰, 高橋 翔, 小川 貴弘, 長谷山 美紀, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 117, 431, 195, 200, 15 Feb. 2018
電子情報通信学会, Japanese - A Note on Recurrent Neural Network-based Tactics Estimation in Soccer Videos
鈴木 元樹, 高橋 翔, 小川 貴弘, 長谷山 美紀, 映像情報メディア学会技術報告 = ITE technical report, 42, 4, 131, 135, Feb. 2018
映像情報メディア学会, Japanese - A Study on Active Net-based Estimation of Pass Region in Rugby Videos
高橋 翔, 長谷山 美紀, 映像情報メディア学会技術報告 = ITE technical report, 42, 4, 137, 142, Feb. 2018
映像情報メディア学会, Japanese - Trial Introduction of Convolutional Sparse Coding for Accurate Distress Classification of Road Structures
前田 圭介, 高橋 翔, 小川 貴弘, 長谷山 美紀, 映像情報メディア学会技術報告 = ITE technical report, 42, 4, 189, 194, Feb. 2018
映像情報メディア学会, Japanese - A note on accurate retrieval of similar inspection records based on canonical correlation between eye tracking data and inspection records
斉藤 僚汰, 高橋 翔, 小川 貴弘, 長谷山 美紀, 映像情報メディア学会技術報告 = ITE technical report, 42, 4, 195, 200, Feb. 2018
映像情報メディア学会, Japanese - Leading edge of Education for Mathematical and Data Science in Hokkaido University-Implementation of a Custom-made Practical Education Program-
長谷山美紀, 大本亨, 高橋翔, 長谷山美紀, 大本亨, 電子情報通信学会技術研究報告, 117, 431(ITS2017 61-83), 2018 - Leading edge of Education for Mathematical and Data Science in Hokkaido University-Implementation of General Education Program and Specialized Education Program-
長谷山美紀, 大本亨, 高橋翔, 長谷山美紀, 大本亨, 電子情報通信学会技術研究報告, 117, 431(ITS2017 61-83), 2018 - Trends of Education and Research for Mathematical and Data Science-Implementation in Education and Research Center for Mathematical and Data Science, Hokkaido University-
長谷山美紀, 大本亨, 高橋翔, 長谷山美紀, 大本亨, 電子情報通信学会技術研究報告, 117, 431(ITS2017 61-83), 2018 - 複数の分類器から得られる確信度に注目したサッカー映像における重要シーンの検出に関する検討
春山知生, 高橋翔, 小川貴弘, 長谷山美紀, 電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 2018, 2018 - 深層学習に基づく特徴量を用いたサッカー映像に撮像されたフィールド位置の推定に関する検討
鈴木元樹, 高橋翔, 小川貴弘, 長谷山美紀, 電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 2018, 2018 - テンソル補完に基づいたユーザの動作からの関心度推定に関する検討
九島哲哉, 高橋翔, 小川貴弘, 長谷山美紀, 電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 2018, 2018 - A Study on Detection of Similar Scenes based on Player Positions in Soccer Video
髙橋 翔, 長谷山 美紀, 映像情報メディア学会技術報告 = ITE technical report, 41, 41, 5, 8, Nov. 2017
映像情報メディア学会, Japanese - ランク最小化に基づく行列補完を用いた関心度推定の高精度化に関する検討
九島哲哉, 高橋翔, 小川貴弘, 長谷山美紀, 電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 2017, ROMBUNNO.113, 28 Oct. 2017
Japanese - 正準相関最大化を導入した深層学習に基づく送電鉄塔の劣化レベル分類に関する検討 (メディア工学) -- (サマーセミナー2017 : 世界に羽ばたくビジョン技術)
前田 圭介, 高橋 翔, 小川 貴弘, 長谷山 美紀, 映像情報メディア学会技術報告 = ITE technical report, 41, 29, 11, 14, Sep. 2017
映像情報メディア学会, Japanese - Deep Extreme Learning Machineに基づくサッカー映像に撮像されたフィールド位置の推定に関する検討 (メディア工学) -- (サマーセミナー2017 : 世界に羽ばたくビジョン技術)
鈴木 元樹, 高橋 翔, 小川 貴弘, 長谷山 美紀, 映像情報メディア学会技術報告 = ITE technical report, 41, 29, 25, 28, Sep. 2017
映像情報メディア学会, Japanese - 変状評価支援のための類似点検データ検索の高精度化に関する検討 : 熟練技術者の判定に関する推定に基づいた学習データ生成法の導入 (メディア工学) -- (サマーセミナー2017 : 世界に羽ばたくビジョン技術)
斉藤 僚汰, 高橋 翔, 小川 貴弘, 長谷山 美紀, 映像情報メディア学会技術報告 = ITE technical report, 41, 29, 49, 52, Sep. 2017
映像情報メディア学会, Japanese - A Study on Object Extraction in Steel Tower Videos Shot by Inspection of Transmission Line Tower
館農 浩平, 高橋 翔, 小川 貴弘, 長谷山 美紀, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 116, 463, 25, 30, 20 Feb. 2017
電子情報通信学会, Japanese - A Note on Selection of Representative Images for Deterioration Diagnosis of Steel Tower
藤後 廉, 高橋 翔, 小川 貴弘, 長谷山 美紀, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 116, 463, 47, 50, 20 Feb. 2017
電子情報通信学会, Japanese - A Note on Accurate Distress Classification for Maintenance Inspection of Road Structures via Deep Learning
前田 圭介, 高橋 翔, 小川 貴弘, 長谷山 美紀, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 116, 463, 51, 54, 20 Feb. 2017
電子情報通信学会, Japanese - A Note on Deformation Detection in Subway Tunnel Using Convolutional Neural Network
石原 賢太, 高橋 翔, 小川 貴弘, 長谷山 美紀, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 116, 463, 81, 86, 20 Feb. 2017
電子情報通信学会, Japanese - A Study on Object Extraction in Steel Tower Videos Shot by Inspection of Transmission Line Tower
館農 浩平, 高橋 翔, 小川 貴弘, 長谷山 美紀, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 116, 464, 25, 30, 20 Feb. 2017
電子情報通信学会, Japanese - A Note on Selection of Representative Images for Deterioration Diagnosis of Steel Tower
藤後 廉, 高橋 翔, 小川 貴弘, 長谷山 美紀, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 116, 464, 47, 50, 20 Feb. 2017
電子情報通信学会, Japanese - A Note on Accurate Distress Classification for Maintenance Inspection of Road Structures via Deep Learning
前田 圭介, 高橋 翔, 小川 貴弘, 長谷山 美紀, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 116, 464, 51, 54, 20 Feb. 2017
電子情報通信学会, Japanese - A Note on Deformation Detection in Subway Tunnel Using Convolutional Neural Network
石原 賢太, 高橋 翔, 小川 貴弘, 長谷山 美紀, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 116, 464, 81, 86, 20 Feb. 2017
電子情報通信学会, Japanese - A Study on Object Extraction in Steel Tower Videos Shot by Inspection of Transmission Line Tower
館農 浩平, 高橋 翔, 小川 貴弘, 長谷山 美紀, 映像情報メディア学会技術報告 = ITE technical report, 41, 5, 25, 30, Feb. 2017
映像情報メディア学会, Japanese - A Note on Selection of Representative Images for Deterioration Diagnosis of Steel Tower
藤後 廉, 高橋 翔, 小川 貴弘, 長谷山 美紀, 映像情報メディア学会技術報告 = ITE technical report, 41, 5, 47, 50, Feb. 2017
映像情報メディア学会, Japanese - A Note on Accurate Distress Classification for Maintenance Inspection of Road Structures via Deep Learning
前田 圭介, 高橋 翔, 小川 貴弘, 長谷山 美紀, 映像情報メディア学会技術報告 = ITE technical report, 41, 5, 51, 54, Feb. 2017
映像情報メディア学会, Japanese - A Note on Deformation Detection in Subway Tunnel Using Convolutional Neural Network
石原 賢太, 高橋 翔, 小川 貴弘, 長谷山 美紀, 映像情報メディア学会技術報告 = ITE technical report, 41, 5, 81, 86, Feb. 2017
映像情報メディア学会, Japanese - [Paper] A Method of Important Player Extraction Based on Link Analysis in Soccer Videos
Takahashi Sho, Haseyama Miki, ITE Transactions on Media Technology and Applications, 5, 2, 42, 48, 2017
In this paper, a method for extraction of important players in soccer videos based on link analysis is proposed. In a soccer match, players perform shoot tackles, assistance, and covering. Furthermore, the soccer tactics are defined the formation of players based on various relationships between players. The proposed method extracts the important players, in order to obtain information for understanding the soccer matches for various audiences. Specifically, our method notes that relationship between players, who cooperate with each other by the pass and the covering, is similar to relationship between web pages which are connected by links. First, the proposed method obtains player networks based on relationship between players in each team. The relationships are defined based on player positions and the possibility of the pass or the covering between players. Finally, in the proposed method, by applying the link analysis to the obtained player networks, important players are extracted. By realizing this approach, important players are extracted from the player networks based on the possibility of the pass or the covering between players. In the last of this paper, the above link analysis-based method was applied to actual soccer matches to show the reasonability of our method., The Institute of Image Information and Television Engineers, English - 深層学習によって得られる画像特徴量を用いた道路構造物の点検データ検索の高精度化に関する検討
斉藤僚汰, 高橋翔, 小川貴弘, 長谷山美紀, 電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 2016, ROMBUNNO.114, 05 Nov. 2016
Japanese - 高速道路の維持管理における点検記録データ検索に対する技術者の評価を用いた検索精度向上に関する検討
高橋翔, 小川貴弘, 長谷山美紀, 映像情報メディア学会年次大会講演予稿集(CD-ROM), 2016, ROMBUNNO.22B‐1, 17 Aug. 2016
Japanese - A Note on Data Analysis for Supporting Distress Evaluation in Expressway Maintenance : Retrieval of Similar Inspection Records Using Distress Images
三改木 裕矢, 高橋 翔, 小川 貴弘, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 115, 458, 169, 172, 22 Feb. 2016
電子情報通信学会, Japanese - A Trial of Gaze Data Acquisition in Embankment Inspection of River Management
三改木 裕矢, 高橋 翔, 小川 貴弘, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 115, 459, 173, 176, 22 Feb. 2016
電子情報通信学会, Japanese - A Note on Analysis of Gaze Data and Skill of Inspector in Embankment Inspection
高橋 翔, 三改木 裕矢, 小川 貴弘, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 115, 458, 177, 180, 22 Feb. 2016
電子情報通信学会, Japanese - A Note on Accurate Distress Classification for Maintenance Inspection of Road Structures : Integration of Multiple Classification Results based on Tag Data and Distress Images
前田 圭介, 高橋 翔, 小川 貴弘, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 115, 459, 181, 184, 22 Feb. 2016
電子情報通信学会, Japanese - A Note on Data Analysis for Supporting Distress Evaluation in Expressway Maintenance : Retrieval of Similar Inspection Records Using Distress Images
三改木 裕矢, 高橋 翔, 小川 貴弘, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 115, 459, 169, 172, 22 Feb. 2016
電子情報通信学会, Japanese - A Trial of Gaze Data Acquisition in Embankment Inspection of River Management
三改木 裕矢, 高橋 翔, 小川 貴弘, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 115, 458, 173, 176, 22 Feb. 2016
電子情報通信学会, Japanese - A Note on Accurate Distress Classification for Maintenance Inspection of Road Structures : Integration of Multiple Classification Results based on Tag Data and Distress Images
前田 圭介, 高橋 翔, 小川 貴弘, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 115, 458, 181, 184, 22 Feb. 2016
電子情報通信学会, Japanese - A Note on Data Analysis for Supporting Distress Evaluation in Expressway Maintenance : Retrieval of Similar Inspection Records Using Distress Images
三改木 裕矢, 高橋 翔, 小川 貴弘, 長谷山 美紀, 映像情報メディア学会技術報告 = ITE technical report, 40, 6, 169, 172, Feb. 2016
映像情報メディア学会, Japanese - A Trial of Gaze Data Acquisition in Embankment Inspection of River Management
三改木 裕矢, 高橋 翔, 小川 貴弘, 秋山 泰祐, 巖倉 啓子, 長谷山 美紀, 映像情報メディア学会技術報告 = ITE technical report, 40, 6, 173, 176, Feb. 2016
映像情報メディア学会, Japanese - A Note on Analysis of Gaze Data and Skill of Inspector in Embankment Inspection
高橋 翔, 三改木 裕矢, 小川 貴弘, 長谷山 美紀, 映像情報メディア学会技術報告 = ITE technical report, 40, 6, 177, 180, Feb. 2016
映像情報メディア学会, Japanese - A Note on Accurate Distress Classification for Maintenance Inspection of Road Structures : Integration of Multiple Classification Results based on Tag Data and Distress Images
前田 圭介, 高橋 翔, 小川 貴弘, 長谷山 美紀, 映像情報メディア学会技術報告 = ITE technical report, 40, 6, 181, 184, Feb. 2016
映像情報メディア学会, Japanese - Retrieval of Similar Inspection Records Based on Metric Learning Using Fixperienced Inspectors' Evaluation
Ryota Saito, Sho Takahashi, Takahiro Ogawa, Miki Hasayama, 2016 IEEE 5TH GLOBAL CONFERENCE ON CONSUMER ELECTRONICS, 2016, GCCE, 1‐2, 2, 2016
This paper presents a retrieval method of similar inspection records in road structures based on metric learning using experienced inspectors' evaluation. Inspection records of road structures include images and text-based information such as category of distress, damaged parts and degree of damage. The proposed method calculates distances from query inspection records, and rank lists of retrieval results are obtained for each feature. In this approach, the distance quantification are updated on the basis of experienced inspectors' evaluation. Finally, the proposed method obtains retrieval results by integrating the multiple rank lists. The experimental results show the effectiveness of the proposed method., IEEE, English - Decision Level Fusion-based Team Tactics Estimation in Soccer Videos
Genki Suzuki, Sho Takahashi, Takahiro Ogawa, Miki Haseyama, 2016 IEEE 5TH GLOBAL CONFERENCE ON CONSUMER ELECTRONICS, 2016, GCCE, 1‐2, 2016
A decision-level fusion (DLF)-based team tactics estimation method in soccer videos is newly presented. In our method, tactics estimation based on audio-visual and formation features is newly adopted since the tactics of the soccer game are closely related to the audio-visual sequences and player positions. Therefore, by using these features, we classify the tactics via Support. Vector Machine (SVM). Furthermore, by applying DIA' to the SVM-based classification results, the two modalities are integrated to obtain more accurate tactics estimation results. Some results of experiments verify the superiority of our method., IEEE, English - [Paper] DLF-based Speech Segment Detection and Its Application to Audio Noise Removal for Video Conferences
Sasaki Kazuto, Ogawa Takahiro, Takahashi Sho, Haseyama Miki, ITE Transactions on Media Technology and Applications, 4, 1, 68, 77, 2016
A new decision-level fusion (DLF)-based speech segment detection method and its application to audio noise removal for video conferences are presented in this paper. The proposed method calculates visual and audio features from video sequences and audio signals, respectively, obtained in video conferences. Features extracted from mouth regions of participants and attribution degrees of speech class are used as visual and audio features, respectively, and Support Vector Machine (SVM)-based classification is performed by using each kind of feature. The SVM classifier performs two-class classification of speech and non-speech segments to realize speech segment detection. From the detection results obtained from the visual and audio features, DLF based on Supervised Learning from Multiple Experts is performed to successfully obtain the final detection results with focus on the accuracy of each detection result. Then, from audio signals in the non-speech segments detected by our method, we can extract noise information to realize accurate audio noise removal in the speech segments., The Institute of Image Information and Television Engineers, English - A Study on Detection of Similar Scenes based on Pass Regions in Soccer Videos
TAKAHASHI Sho, HASEYAMA Miki, ITE Technical Report, 40, 0, 9, 12, 2016
This paper proposes a pass region-based method for detecting similar scenes in soccer videos. In the soccer games, since the pass is very useful for analyses of various soccer tactics, the visualization of the pass regions is a very important task. Generally, since the tactics are defined by the formation of players, in the case of same tactic in two soccer scenes, the pass course is considered to be similar. Therefore, in this paper, we propose a detection method of similar scenes by utilizing the pass regions in soccer videos., The Institute of Image Information and Television Engineers, Japanese - サッカー映像における試合内容の理解を促すデータの提示に関する検討
高橋翔, 長谷山美紀, 電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 2015, ROMBUNNO.135, 07 Nov. 2015
Japanese - 道路構造物の変状画像に対する類似検索の高精度化に関する検討
高橋翔, 小川貴弘, 長谷山美紀, 電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 2015, ROMBUNNO.134, 07 Nov. 2015
Japanese - 個々の道路構造物に関する点検項目の導入による道路構造物の変状推定の高精度化に関する検討
前田圭介, 高橋翔, 小川貴弘, 長谷山美紀, 電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 2015, ROMBUNNO.133, 07 Nov. 2015
Japanese - A Note on Data Analysis for Maintenance Inspection of Infrastructures : Quantification of Relationship between Inspection Data Using Distress Images and Inspection Results
三改木 裕矢, 高橋 翔, 小川 貴弘, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 114, 459, 257, 262, 23 Feb. 2015
電子情報通信学会, Japanese - A Note on Data Analysis for Maintenance Inspection of Infrastructures : Quantification of Relationship between Inspection Data Using Distress Images and Inspection Results
三改木 裕矢, 高橋 翔, 小川 貴弘, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 114, 460, 257, 262, 23 Feb. 2015
電子情報通信学会, Japanese - A Note on Data Analysis for Maintenance Inspection of Infrastructures : Quantification of Relationship between Inspection Data Using Distress Images and Inspection Results
三改木 裕矢, 高橋 翔, 小川 貴弘, 映像情報メディア学会技術報告 = ITE technical report, 39, 7, 257, 262, Feb. 2015
映像情報メディア学会, Japanese - A Study on High Performance Parallel Computing for Active Net-based Pass Region Estimation in Soccer Videos
TAKAHASHI Sho, HASEYAMA Miki, ITE Technical Report, 39, 0, 1, 6, 2015
This paper proposes a high performance parallel computing for Active net-based pass region estimation in soccer videos. In the soccer games, since the pass is very useful for analyses of various soccer tactics, the visualization of the pass regions is a very important task. Therefore, the pass region estimation method based on Active net is proposed. However, computation time of the pass region estimation must be reduced. Thus, in this paper, we propose a high performance parallel computing for Active net-based pass region estimation. By utilizing CUDA^as the computation environment, the high performance parallel computing is realized., The Institute of Image Information and Television Engineers, Japanese - A Note on Estimation of Group Advantage for Group Tactics Analysis in Soccer Videos
TAKAHASHI Sho, HASEYAMA Miki, ITE Technical Report, 39, 0, 7, 12, 2015
This paper reports a effectiveness of the estimation method of group advantage in soccer videos. The group advantage represents the degree of team's superiority or inferiority in each group. For this analysis, the proposed method classifies players into some groups. As a result of this classification, the players in one group are closely related in terms of soccer tactics. In this method, the relationship between the players in the groups are analyzed by using player positions. Then, this method estimates group advantages by utilizing the relationship of the players. In the last of this paper, by utilizing the actual soccer videos, we evaluate the estimation method of the group advantage., The Institute of Image Information and Television Engineers, Japanese - 複数の画像特徴を用いたベイジアンネットワークに基づく構造物の変状の推定の高精度化に関する検討
MAEDA KEISUKE, TAKAHASHI SHO, OGAWA TAKAHIRO, HASEYAMA MIKI, 電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 2014, ROMBUNNO.140, 25 Oct. 2014
Japanese - 維持管理業務の効率化に向けた点検データの類似度算出における特徴選択に関する検討
MIKAIKI YUYA, TAKAHASHI SHO, OGAWA TAKAHIRO, HASEYAMA MIKI, 電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 2014, ROMBUNNO.139, 25 Oct. 2014
Japanese - A Note on Estimating Deformation Based on Bayesian Networks Using Images from Bridge Inspection
小林 克希, 高橋 翔, 小川 貴弘, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 113, 434, 217, 221, 17 Feb. 2014
電子情報通信学会, Japanese - Definition of Soccer Player's Features Using Network Analysis and Its Application to Similarity Calculation between Players
岩井 和也, 高橋 翔, 小川 貴弘, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 113, 434, 319, 324, 17 Feb. 2014
電子情報通信学会, Japanese - A Note on Estimating Deformation Based on Bayesian Networks Using Images from Bridge Inspection
小林 克希, 高橋 翔, 小川 貴弘, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 113, 433, 217, 221, 17 Feb. 2014
電子情報通信学会, Japanese - Definition of Soccer Player's Features Using Network Analysis and Its Application to Similarity Calculation between Players
岩井 和也, 高橋 翔, 小川 貴弘, 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 113, 433, 319, 324, 17 Feb. 2014
電子情報通信学会, Japanese - A Note on Estimating Deformation Based on Bayesian Networks Using Images from Bridge Inspection
小林 克希, 高橋 翔, 小川 貴弘, 映像情報メディア学会技術報告 = ITE technical report, 38, 7, 217, 221, Feb. 2014
映像情報メディア学会, Japanese - Definition of Soccer Player's Features Using Network Analysis and Its Application to Similarity Calculation between Players
岩井 和也, 高橋 翔, 小川 貴弘, 映像情報メディア学会技術報告 = ITE technical report, 38, 7, 319, 324, Feb. 2014
映像情報メディア学会, Japanese - A Note on Network Analysis Based Detection of Important Player and Similar Scenes in Soccer Videos
TAKAHASHI Sho, HASEYAMA Miki, ITE Technical Report, 38, 0, 1, 4, 2014
This paper proposes a link analysis-based method for detecting important players and similar scenes in soccer videos. We define important players as follows: 1) the attacking player who have great relevancy to a score, 2) the defending player on the opposing team, and 3) players who assist the above players. Since soccer tactic analysis focuses not only on player skill but also relationships between players, this paper expresses the relationships between players as a network, which is constructed from player positions in the soccer video. The proposed method analyses the constructed network to detect important players and similar scenes., The Institute of Image Information and Television Engineers, Japanese - ベイジアンネットワークを用いた構造物の点検データからの変状の推定
小林克希, 高橋翔, 小川貴弘, 長谷山美紀, 電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 2013, ROMBUNNO.173, 19 Oct. 2013
Japanese - Player Tracking by Using Level-Set Method in Soccer Video
TAKAHASHI Sho, LIM Wonkuk, HASEYAMA Miki, The IEICE transactions on information and systems (Japanese edetion), 96, 3, 695, 703, 01 Mar. 2013
本論文では,サッカー映像からレベルセット法を用いて選手を追跡する手法を提案する.提案手法では,サッカー映像を各フレームが時間軸方向に重なるように連結した三次元データとして扱う.このデータに対して,レベルセット法を適用することで抽出される三次元の領域は,複数フレームに渡って存在する同一選手を包含する.提案手法では,この三次元の領域をサッカー映像から抽出することで,選手の追跡を実現する.したがって,提案手法では,フレームごとに選手を検出する必要がないため,フレームを個別に処理する従来手法における選手の検出と追跡それぞれの誤差によって精度が低下する問題を解決可能である.また,我々は,ユニフォームの色成分をサッカー映像から色コリログラムを用いて推定し,これをレベルセット法を用いて追跡する選手の特徴として導入する.これにより,提案手法では,追跡対象の特徴を事前に与えることなく,選手の頑健な追跡が可能となる.本文の最後では,実際にテレビで放送されたサッカー映像に対する実験により,提案手法の有効性を確認する., The Institute of Electronics, Information and Communication Engineers, Japanese - A Note on Soccer Player Tracking Using Elastic Model : Performance Improvement Based on New Potential Energy
岩井 和也, 高橋 翔, 小川 貴弘, 電子情報通信学会技術研究報告 : 信学技報, 112, 434, 135, 139, 18 Feb. 2013
電子情報通信学会, Japanese - A Note on Accurate Estimation of Pitcher's Condition in Baseball Videos : Improvement of Features Based on Pitching Motions and Pitching Results
久保 純貴, 高橋 翔, 小川 貴弘, 電子情報通信学会技術研究報告 : 信学技報, 112, 434, 141, 146, 18 Feb. 2013
電子情報通信学会, Japanese - A Note on Accurate Soccer Video Segmentation Based on the Team Possessing the Ball
大貫 修平, 高橋 翔, 小川 貴弘, 電子情報通信学会技術研究報告 : 信学技報, 112, 434, 147, 151, 18 Feb. 2013
電子情報通信学会, Japanese - A Study on an Accurate Method for Estimating Pass Region from Soccer Video : Definition of a New Evaluation Function Based on Changes in Player Position Geometry over Time
高橋 翔, 長谷山 美紀, 電子情報通信学会技術研究報告 : 信学技報, 112, 434, 153, 158, 18 Feb. 2013
電子情報通信学会, Japanese - A Note on Soccer Player Tracking Using Elastic Model : Performance Improvement Based on New Potential Energy
岩井 和也, 高橋 翔, 小川 貴弘, 電子情報通信学会技術研究報告 : 信学技報, 112, 433, 135, 139, 18 Feb. 2013
電子情報通信学会, Japanese - A Note on Accurate Estimation of Pitcher's Condition in Baseball Videos : Improvement of Features Based on Pitching Motions and Pitching Results
久保 純貴, 高橋 翔, 小川 貴弘, 電子情報通信学会技術研究報告 : 信学技報, 112, 433, 141, 146, 18 Feb. 2013
電子情報通信学会, Japanese - A Note on Accurate Soccer Video Segmentation Based on the Team Possessing the Ball
大貫 修平, 高橋 翔, 小川 貴弘, 電子情報通信学会技術研究報告 : 信学技報, 112, 433, 147, 151, 18 Feb. 2013
電子情報通信学会, Japanese - A Study on an Accurate Method for Estimating Pass Region from Soccer Video : Definition of a New Evaluation Function Based on Changes in Player Position Geometry over Time
高橋 翔, 長谷山 美紀, 電子情報通信学会技術研究報告 : 信学技報, 112, 433, 153, 158, 18 Feb. 2013
電子情報通信学会, Japanese - A Note on Soccer Player Tracking Using Elastic Model : Performance Improvement Based on New Potential Energy
岩井 和也, 高橋 翔, 小川 貴弘, 映像情報メディア学会技術報告 = ITE technical report, 37, 8, 135, 139, Feb. 2013
映像情報メディア学会, Japanese - A Note on Accurate Estimation of Pitcher's Condition in Baseball Videos : Improvement of Features Based on Pitching Motions and Pitching Results
久保 純貴, 高橋 翔, 小川 貴弘, 映像情報メディア学会技術報告 = ITE technical report, 37, 8, 141, 146, Feb. 2013
映像情報メディア学会, Japanese - A Note on Accurate Soccer Video Segmentation Based on the Team Possessing the Ball
大貫 修平, 高橋 翔, 小川 貴弘, 映像情報メディア学会技術報告 = ITE technical report, 37, 8, 147, 151, Feb. 2013
映像情報メディア学会, Japanese - A Study on an Accurate Method for Estimating Pass Region from Soccer Video : Definition of a New Evaluation Function Based on Changes in Player Position Geometry over Time
高橋 翔, 長谷山 美紀, 映像情報メディア学会技術報告 = ITE technical report, 37, 8, 153, 158, Feb. 2013
映像情報メディア学会, Japanese - 変状評価の支援を目的とした点検データの可視化に関する検討
TAKAHASHI SHO, OGAWA TAKAHIRO, HASEYAMA MIKI, 日本道路会議論文集(CD-ROM), 30th, ROMBUNNO.2053, 2013
Japanese - 弾性モデルを用いたサッカー映像における選手追跡の高精度化に関する検討
IWAI KAZUYA, TAKAHASHI SHO, OGAWA TAKAHIRO, HASEYAMA MIKI, 電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 2012, ROMBUNNO.149, 20 Oct. 2012
Japanese - サッカーのチーム戦術推定手法を用いた試合映像の分割に関する検討
ONUKI SHUHEI, TAKAHASHI SHO, OGAWA TAKAHIRO, HASEYAMA MIKI, 電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 2012, ROMBUNNO.148, 20 Oct. 2012
Japanese - A method for detecting important events in soccer videos of amateur teams : An approach using tactical comments added to videos for soccer coaching
高橋 翔, 嶌田 聡, 長谷山 美紀, 電子情報通信学会技術研究報告 : 信学技報, 111, 442, 275, 280, 20 Feb. 2012
電子情報通信学会, Japanese - A Note on Estimation of Pitcher's Condition Based on Pitching Motion in Baseball Video and Scorebook
久保 純貴, 高橋 翔, 小川 貴弘, 電子情報通信学会技術研究報告 : 信学技報, 111, 442, 287, 292, 20 Feb. 2012
電子情報通信学会, Japanese - A method for detecting important events in soccer videos of amateur teams : An approach using tactical comments added to videos for soccer coaching
高橋 翔, 嶌田 聡, 長谷山 美紀, 電子情報通信学会技術研究報告 : 信学技報, 111, 441, 275, 280, 20 Feb. 2012
電子情報通信学会, Japanese - A Note on Estimation of Pitcher's Condition Based on Pitching Motion in Baseball Video and Scorebook
久保 純貴, 高橋 翔, 小川 貴弘, 電子情報通信学会技術研究報告 : 信学技報, 111, 441, 287, 292, 20 Feb. 2012
電子情報通信学会, Japanese - A method for detecting important events in soccer videos of amateur teams : An approach using tactical comments added to videos for soccer coaching
高橋 翔, 嶌田 聡, 長谷山 美紀, 映像情報メディア学会技術報告, 36, 9, 275, 280, Feb. 2012
映像情報メディア学会, Japanese - A Note on Estimation of Pitcher's Condition Based on Pitching Motion in Baseball Video and Scorebook
久保 純貴, 高橋 翔, 小川 貴弘, 映像情報メディア学会技術報告, 36, 9, 287, 292, Feb. 2012
映像情報メディア学会, Japanese - 選手の移動速度を考慮したサッカー映像における3次元パス可能領域の推定に関する検討
高橋翔, 長谷山美紀, 映像情報メディア学会冬季大会講演予稿集(CD-ROM), 2012, 2012 - 8-3 A note on improvement of 3D pass region estimation method using player velocity in soccer videos
TAKAHASHI Sho, HASEYAMA Miki, PROCEEDINGS OF THE ITE WINTER ANNUAL CONVENTION, 2012, 0, 8, 3-1, 2012
This paper realizes an improvement of 3D pass region estimation method by using player velocity in soccer videos. In the previous method, since the pass region was estimated regardless of player velocity, the accuracy was limited. Therefore, by introducing the player velocity to the pass region estimation, we improve the performance of the previous method., The Institute of Image Information and Television Engineers, Japanese - サッカー映像における選手位置抽出結果を用いたチーム戦術の推定に関する検討
ONUKI SHUHEI, TAKAHASHI SHO, OGAWA TAKAHIRO, HASEYAMA MIKI, 電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 2011, ROMBUNNO.154, 22 Oct. 2011
Japanese - 選手動作と歓声の関係性に注目したサッカー映像における重要場面の検出に関する検討
KUBO JUNKI, TAKAHASHI SHO, OGAWA TAKAHIRO, HASEYAMA MIKI, 映像情報メディア学会年次大会講演予稿集(CD-ROM), 2011, ROMBUNNO.8-4, 01 Aug. 2011
Japanese - A Study on Accurate Pass Region Estimation in Soccer Videos : Introduction of Adaptive Parameter Settings
TAKAHASHI Sho, HASEYAMA Miki, IEICE technical report, 110, 420, 77, 82, 14 Feb. 2011
In this paper, an accurate method of pass region estimation method is proposed by introduceing an adaptive parameter settings. We have proposed a pass region estimation method by utilizing average values of ball's velocity and player's velocity. However, velocities of a ball and players are different according to player's density and player's skill. Therefore, in the proposed method, parameters, which are a velocity of a ball and velocities of players, are set by using obtained player's positions from a target soccer video. Consicuently, the accurate method of pass region estimation is realized., The Institute of Electronics, Information and Communication Engineers, Japanese - A Study on Accurate Pass Region Estimation in Soccer Videos : Introduction of Adaptive Parameter Settings
TAKAHASHI Sho, HASEYAMA Miki, IEICE technical report, 110, 421, 77, 82, 14 Feb. 2011
In this paper, an accurate method of pass region estimation method is proposed by introduceing an adaptive parameter settings. We have proposed a pass region estimation method by utilizing average values of ball's velocity and player's velocity. However, velocities of a ball and players are different according to player's density and player's skill. Therefore, in the proposed method, parameters, which are a velocity of a ball and velocities of players, are set by using obtained player's positions from a target soccer video. Consicuently, the accurate method of pass region estimation is realized., The Institute of Electronics, Information and Communication Engineers, Japanese - 色の共起頻度を用いたサッカー映像におけるユニフォームの色成分の推定に関する検討
高橋翔, 長谷山美紀, 映像情報メディア学会年次大会講演予稿集(CD-ROM), 2011, 2011 - 8-5 A Note on Color Component Estimation of Team Uniforms in Soccer Videos based on Color Co-occurrence Histograms
TAKAHASHI Sho, HASEYAMA Miki, PROCEEDINGS OF THE ITE ANNUAL CONVENTION, 2011, 0, 8, 5-1-_8-5-2_, 2011
This paper proposes a color estimation method of team uniforms in soccer videos based on color co-occurrence. The proposed method calculates color correlograms and selects sets of color components, whose co-occurrences are higher than the other sets. This enables the color component estimation of the team uniforms, which contain multiple colors., The Institute of Image Information and Television Engineers, Japanese - 8-4 A note on detection of important events based on relationship between player action and sound on stadium in soccer videos
KUBO Junki, TAKAHASHI Sho, OGAWA Takahiro, HASEYAMA Miki, PROCEEDINGS OF THE ITE ANNUAL CONVENTION, 2011, 0, 8, 4-1-_8-4-2_, 2011
This paper presents a detection method of important events based on relationship between player action and sound on stadium in soccer videos. Generally, since player action and sound on stadium have high correlation in the important events, we realize the detection by using their relationship based on canonical correlation analysis., The Institute of Image Information and Television Engineers, Japanese - A Study on Accurate Pass Region Estimation in Soccer Videos : Introduction of Adaptive Parameter Settings
TAKAHASHI Sho, HASEYAMA Miki, ITE Technical Report, 35, 0, 77, 82, 2011
In this paper, an accurate method of pass region estimation method is proposed by introduceing an adaptive parameter settings. We have proposed a pass region estimation method by utilizing average values of ball's velocity and player's velocity. However, velocities of a ball and players are different according to player's density and player's skill. Therefore, in the proposed method, parameters, which are a velocity of a ball and velocities of players, are set by using obtained player's positions from a target soccer video. Consicuently, the accurate method of pass region estimation is realized., The Institute of Image Information and Television Engineers, Japanese - A Note on 3D Active Grid Based Estimation of 3D Pass Region from Broadcasted Soccer Videos
TAKAHASHI Sho, HASEYAMA Miki, IEICE technical report, 109, 414, 185, 190, 08 Feb. 2010
This paper proposes an estimation method of 3D pass regions from the actual broadcasted soccer videos, where the 3D pass region has a high probability in which the pass succeeds. We have proposed an estimation method of 2D pass regions by using player positions and a ball position, where the player positions and the ball position are obtained as 2D coordinate from the actual broadcasted soccer video. However, the pass regions exist on a 3D space as a region of a 3D shape. Therefore, the proposed method realizes the estimation of the 3D pass region from the 3D space by using the 3D Active Grid. In order to use the 3D Active Grid, new volume data are generated by using player and ball positions, where the volume data indicate a possibility in which players can reach positions in the 3D space. Consequently, this paper realizes the estimation of the pass regions by using the 3D Active Grid., The Institute of Electronics, Information and Communication Engineers, Japanese - A Note on 3D Active Grid Based Estimation of 3D Pass Region from Broadcasted Soccer Videos
TAKAHASHI Sho, HASEYAMA Miki, ITE Technical Report, 34, 0, 185, 190, 2010
This paper proposes an estimation method of 3D pass regions from the actual broadcasted soccer videos, where the 3D pass region has a high probability in which the pass succeeds. We have proposed an estimation method of 2D pass regions by using player positions and a ball position, where the player positions and the ball position are obtained as 2D coordinate from the actual broadcasted soccer video. However, the pass regions exist on a 3D space as a region of a 3D shape. Therefore, the proposed method realizes the estimation of the 3D pass region from the 3D space by using the 3D Active Grid. In order to use the 3D Active Grid, new volume data are generated by using player and ball positions, where the volume data indicate a possibiliy in which players can reach positions in the 3D space. Consequently, this paper realizes the estimation of the pass regions by using the 3D Active Grid., The Institute of Image Information and Television Engineers, Japanese - PLAYERS TRACKING APPROACH USING LEVEL‐SET METHOD BASED ON COLOR COMPONENTS OF PLAYERS IN SOCCER VIDEOS
TAKAHASHI Sho, LIM Wonkuk, HASEYAMA Miki, 画像符号化シンポジウム資料, 25th, 67, 68, 2010
English - アクティブグリッドを用いたサッカー映像におけるパス可能領域の時刻変化の抽出
高橋翔, 第24回信号処理シンポジウム, 2009, 2, 420, 425, 2009 - サッカー映像の意味解析に関する一手法-ネットワーク解析を用いた試合展開における重要選手の抽出-
高橋翔, 第23回信号処理シンポジウム, Nov., 2009, 2009 - アクティブグリッドを用いたサッカー映像におけるパス可能領域の推定に関する検討
高橋翔, 長谷山美紀, 電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 2009, 2009
Lectures, oral presentations, etc.
- 産業分野における人の動きの解析と技術教育 -建設現場映像における作業員の連動性評価-
高橋翔
映像情報メディア学会2022年冬季大会, 23 Dec. 2022, Japanese, Oral presentation - 道路空間のリアルタイムデジタルツインを可能とするEdge-AI
高橋翔
第4回 JSTEシンポジウム, 25 Nov. 2022, Japanese, Oral presentation - 現実世界に活かすVirtual Realityを用いた情報提示の試行とドライバの振る舞いの分析
高橋翔
第4回 JSTEシンポジウム, 24 Nov. 2022, Japanese, Oral presentation - ETC2.0の解析結果による大雪時の札幌市内交通の実態について
高橋翔
2022年度 JWAシンポジウム, 02 Nov. 2022, Japanese, Nominated symposium
[Invited] - Lateral Position of Vehicles on Road in Winter Conditions
Sho Takahashi, Naoyuki Shiraishi, Toru Hagiwara
自動車技術会2022年秋季大会, 13 Oct. 2022, Japanese, Oral presentation - 安全・安心で豊かな未来社会に導くデジタル技術 ~Edge-AIによる映像データ解析と現実世界の定量化~
高橋翔
第40回 技術者交流フォーラム事業in釧路, 06 Oct. 2022, Japanese, Public discourse
[Invited] - A Study on Introduction of Video Analysis AI for Small and Medium Building Contractors and Its Trial
Sho Takahashi, Masahiro Yagi, Tomohiro Mukai, Toru Hagiwara, Kiyotaka Suda, Jevica, Hiroshi Yanase
土木学会 令和4年度全国大会 第77回年次学術講演会, 22 Sep. 2022, Japanese, Oral presentation - Advanced Road Visibility Inspection System for Winter Road Maintenance Using Microcomputer
Sho Takahashi, Toru Hagiwara, Ryo Sato, Kazuhito Ohashi, Yasuhiro Nagata
IEEE 10th Global Conference on Consumer Electronics, Oct. 2021, English, Poster presentation - Vehicle Behavior Measurement based-on RTK-GNSS for Driver’s Risk Feeling Estimation
Sho TAKAHASHI, Shuhei WADA, Toru HAGIWARA, Kazunori MUNEHIRO
IEEE 10th Global Conference on Consumer Electronics, Oct. 2021, English, Oral presentation - 画像・映像データとAI 車両の意味理解 -次世代の道路・交通管理の実現に向けて-
高橋翔
令和3年度 第1回 地域ITS研究会, 27 Sep. 2021, Japanese, Public discourse - 施工の暗黙知を掘り起こす新しい手法 骨格検知とプロファイリング
高橋翔
第20回 産学官CIM・GISセミナー, 09 Jul. 2021, Japanese, Public discourse - 空間周波数および深層学習に基づく機械学習による視程レベル推定-特徴選択手法による空間周波数の選択効果-
髙橋翔, 河田祥太朗, 萩原亨
第63回土木計画学研究発表会, 05 Jun. 2021, Japanese, Oral presentation - 基調講演 「インフラ管理における画像・映像データの意味理解と AI活⽤」
高橋翔
第19回産学官CIM・GISセミナー, 25 Sep. 2020, Japanese, Public discourse
[Invited] - 画像・映像処理を活用した社会基盤マネジメントの支援技術構築に向けた取り組みの紹介
高橋翔
令和元年度第2回道路管理技術委員会, 09 Dec. 2019, Japanese, Others
[Invited] - A Note on Accurate Estimation of Deterioration Levels on Transmission Towers via Deep Learning Using Heterogeneous Features
前田 圭介, 高橋 翔, 小川 貴弘, 長谷山 美紀
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 19 Feb. 2019, Japanese - A Method for Predicting Importance of Attack Players based on Gaze Tracking Data in Soccer Videos
鈴木 元樹, 高橋 翔, 小川 貴弘, 長谷山 美紀
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 19 Feb. 2019, Japanese - A note on interest level estimation for videos using users' behavior based on OpenPose
九島 哲哉, 高橋 翔, 小川 貴弘, 長谷山 美紀
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 19 Feb. 2019, Japanese - A Note on Accurate Estimation of Deterioration Levels on Transmission Towers via Deep Learning Using Heterogeneous Features
前田 圭介, 高橋 翔, 小川 貴弘, 長谷山 美紀
映像情報メディア学会技術報告 = ITE technical report, Feb. 2019, Japanese - A Method for Predicting Importance of Attack Players based on Gaze Tracking Data in Soccer Videos
鈴木 元樹, 高橋 翔, 小川 貴弘, 長谷山 美紀
映像情報メディア学会技術報告 = ITE technical report, Feb. 2019, Japanese - A note on interest level estimation for videos using users' behavior based on OpenPose
九島 哲哉, 高橋 翔, 小川 貴弘, 長谷山 美紀
映像情報メディア学会技術報告 = ITE technical report, Feb. 2019, Japanese - Estimation of users’ interest levels using tensor completion with SemiCCA
Kushima Tetsuya, Takahashi Sho, Ogawa Takahiro, Haseyama Miki
IEEE Conference Proceedings, 2019, English - Multi-feature Fusion Based on Supervised Multi-view Multi-label Canonical Correlation Projection
Maeday Keisuke, Takahashi Sho, Ogaway Takahiro, Haseyama Miki
IEEE Conference Proceedings, 2019, English - A Note on Recurrent Neural Network-based Tactics Estimation in Soccer Videos
鈴木 元樹, 高橋 翔, 小川 貴弘, 長谷山 美紀
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 15 Feb. 2018, Japanese - A Study on Active Net-based Estimation of Pass Region in Rugby Videos
高橋 翔, 長谷山 美紀
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 15 Feb. 2018, Japanese - Trial Introduction of Convolutional Sparse Coding for Accurate Distress Classification of Road Structures
前田 圭介, 高橋 翔, 小川 貴弘, 長谷山 美紀
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 15 Feb. 2018, Japanese - A note on accurate retrieval of similar inspection records based on canonical correlation between eye tracking data and inspection records
斉藤 僚汰, 高橋 翔, 小川 貴弘, 長谷山 美紀
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 15 Feb. 2018, Japanese - A Note on Recurrent Neural Network-based Tactics Estimation in Soccer Videos
鈴木 元樹, 高橋 翔, 小川 貴弘, 長谷山 美紀
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 15 Feb. 2018, Japanese - A Study on Active Net-based Estimation of Pass Region in Rugby Videos
高橋 翔, 長谷山 美紀
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 15 Feb. 2018, Japanese - Trial Introduction of Convolutional Sparse Coding for Accurate Distress Classification of Road Structures
前田 圭介, 高橋 翔, 小川 貴弘, 長谷山 美紀
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 15 Feb. 2018, Japanese - A note on accurate retrieval of similar inspection records based on canonical correlation between eye tracking data and inspection records
斉藤 僚汰, 高橋 翔, 小川 貴弘, 長谷山 美紀
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 15 Feb. 2018, Japanese - A Note on Recurrent Neural Network-based Tactics Estimation in Soccer Videos
鈴木 元樹, 高橋 翔, 小川 貴弘, 長谷山 美紀
映像情報メディア学会技術報告 = ITE technical report, Feb. 2018, Japanese - A Study on Active Net-based Estimation of Pass Region in Rugby Videos
高橋 翔, 長谷山 美紀
映像情報メディア学会技術報告 = ITE technical report, Feb. 2018, Japanese - Trial Introduction of Convolutional Sparse Coding for Accurate Distress Classification of Road Structures
前田 圭介, 高橋 翔, 小川 貴弘, 長谷山 美紀
映像情報メディア学会技術報告 = ITE technical report, Feb. 2018, Japanese - A note on accurate retrieval of similar inspection records based on canonical correlation between eye tracking data and inspection records
斉藤 僚汰, 高橋 翔, 小川 貴弘, 長谷山 美紀
映像情報メディア学会技術報告 = ITE technical report, Feb. 2018, Japanese - Estimation of Important Scenes in Soccer Videos Based on Collaborative Use of Audio-Visual CNN Features
Haruyama Tomoki, Takahashi Sho, Ogawa Takahiro, Haseyama Miki
IEEE Conference Proceedings, 2018, English - Team Tactics Estimation in Soccer Videos via Deep Extreme Learning Machine Based on Players Formation
Suzuki Genki, Takahashi Sho, Ogawa Takahiro, Haseyama Miki
IEEE Conference Proceedings, 2018, English - Interest Level Estimation of Items via Matrix Completion Based on Adaptive User Matrix Construction.
Tetsuya Kushima, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
2018 IEEE International Conference on Multimedia and Expo, ICME 2018, San Diego, CA, USA, July 23-27, 2018, 2018, English - A Study on Detection of Similar Scenes based on Player Positions in Soccer Video
髙橋 翔, 長谷山 美紀
映像情報メディア学会技術報告 = ITE technical report, Nov. 2017, Japanese - 正準相関最大化を導入した深層学習に基づく送電鉄塔の劣化レベル分類に関する検討 (メディア工学) -- (サマーセミナー2017 : 世界に羽ばたくビジョン技術)
前田 圭介, 高橋 翔, 小川 貴弘, 長谷山 美紀
映像情報メディア学会技術報告 = ITE technical report, Sep. 2017, Japanese - Deep Extreme Learning Machineに基づくサッカー映像に撮像されたフィールド位置の推定に関する検討 (メディア工学) -- (サマーセミナー2017 : 世界に羽ばたくビジョン技術)
鈴木 元樹, 高橋 翔, 小川 貴弘, 長谷山 美紀
映像情報メディア学会技術報告 = ITE technical report, Sep. 2017, Japanese - 変状評価支援のための類似点検データ検索の高精度化に関する検討 : 熟練技術者の判定に関する推定に基づいた学習データ生成法の導入 (メディア工学) -- (サマーセミナー2017 : 世界に羽ばたくビジョン技術)
斉藤 僚汰, 高橋 翔, 小川 貴弘, 長谷山 美紀
映像情報メディア学会技術報告 = ITE technical report, Sep. 2017, Japanese - Distress classification of road structures via decision level fusion
Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
International Conference on Digital Signal Processing, DSP, 01 Mar. 2017
© 2016 IEEE.A distress classification method of road structures via decision level fusion is presented in this paper. In order to classify various kinds of distresses accurately, the proposed method integrates multiple classification results with considering their performance, and this is the biggest contribution of this paper. By introducing this approach, it becomes feasible to adaptively integrate the multiple classification results based on the accuracy of each classifier for a target sample. Consequently, realization of the accurate distress classification can be expected. Experimental results show that our method outperforms existing methods. - A Study on Object Extraction in Steel Tower Videos Shot by Inspection of Transmission Line Tower
館農 浩平, 高橋 翔, 小川 貴弘, 長谷山 美紀
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 20 Feb. 2017, Japanese - A Note on Selection of Representative Images for Deterioration Diagnosis of Steel Tower
藤後 廉, 高橋 翔, 小川 貴弘, 長谷山 美紀
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 20 Feb. 2017, Japanese - A Note on Accurate Distress Classification for Maintenance Inspection of Road Structures via Deep Learning
前田 圭介, 高橋 翔, 小川 貴弘, 長谷山 美紀
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 20 Feb. 2017, Japanese - A Note on Deformation Detection in Subway Tunnel Using Convolutional Neural Network
石原 賢太, 高橋 翔, 小川 貴弘, 長谷山 美紀
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 20 Feb. 2017, Japanese - A Study on Object Extraction in Steel Tower Videos Shot by Inspection of Transmission Line Tower
館農 浩平, 高橋 翔, 小川 貴弘, 長谷山 美紀
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 20 Feb. 2017, Japanese - A Note on Selection of Representative Images for Deterioration Diagnosis of Steel Tower
藤後 廉, 高橋 翔, 小川 貴弘, 長谷山 美紀
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 20 Feb. 2017, Japanese - A Note on Accurate Distress Classification for Maintenance Inspection of Road Structures via Deep Learning
前田 圭介, 高橋 翔, 小川 貴弘, 長谷山 美紀
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 20 Feb. 2017, Japanese - A Note on Deformation Detection in Subway Tunnel Using Convolutional Neural Network
石原 賢太, 高橋 翔, 小川 貴弘, 長谷山 美紀
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 20 Feb. 2017, Japanese - A Study on Object Extraction in Steel Tower Videos Shot by Inspection Transmission Line Tower
館農浩平, 高橋翔, 小川貴弘, 長谷山美紀
電子情報通信学会技術研究報告, 13 Feb. 2017, Japanese - A Note on Selection of Representative Images for Deterioration Diagnosis of Steel Tower
藤後廉, 高橋翔, 小川貴弘, 長谷山美紀
電子情報通信学会技術研究報告, 13 Feb. 2017, Japanese - A Note on Deformation Detection in Subway Tunnel Using Convolutional Neural Network
石原賢太, 高橋翔, 小川貴弘, 長谷山美紀
電子情報通信学会技術研究報告, 13 Feb. 2017, Japanese - A Note on Accurate Distress Classification for Maintenance Inspection of Road Structures via Deep Learning
前田圭介, 高橋翔, 小川貴弘, 長谷山美紀
電子情報通信学会技術研究報告, 13 Feb. 2017, Japanese - A Study on Object Extraction in Steel Tower Videos Shot by Inspection of Transmission Line Tower
館農 浩平, 高橋 翔, 小川 貴弘, 長谷山 美紀
映像情報メディア学会技術報告 = ITE technical report, Feb. 2017, Japanese - Automatic estimation of deterioration level on transmission towers via deep extreme learning machine based on local receptive field
Maeda Keisuke, Takahashi Sho, Ogawa Takahiro, Haseyama Miki
IEEE Conference Proceedings, 2017, English - Decision level fusion-based team tactics estimation in soccer videos
Genki Suzuki, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
2016 IEEE 5th Global Conference on Consumer Electronics, GCCE 2016, 27 Dec. 2016, English
© 2016 IEEE.A decision-level fusion (DLF)-based team tactics estimation method in soccer videos is newly presented. In our method, tactics estimation based on audio-visual and formation features is newly adopted since the tactics of the soccer game are closely related to the audio-visual sequences and player positions. Therefore, by using these features, we classify the tactics via Support Vector Machine (SVM). Furthermore, by applying DLF to the SVM-based classification results, the two modalities are integrated to obtain more accurate tactics estimation results. Some results of experiments verify the superiority of our method. - Retrieval of similar inspection records based on metric learning using experienced inspectors' evaluation
Ryota Saito, Sho Takahashi, Takahiro Ogawa, Miki Hasayama
2016 IEEE 5th Global Conference on Consumer Electronics, GCCE 2016, 27 Dec. 2016
© 2016 IEEE.This paper presents a retrieval method of similar inspection records in road structures based on metric learning using experienced inspectors' evaluation. Inspection records of road structures include images and text-based information such as category of distress, damaged parts and degree of damage. The proposed method calculates distances from query inspection records, and rank lists of retrieval results are obtained for each feature. In this approach, the distance quantification are updated on the basis of experienced inspectors' evaluation. Finally, the proposed method obtains retrieval results by integrating the multiple rank lists. The experimental results show the effectiveness of the proposed method. - A Study on Detection of Similar Scenes based on Pass Regions in Soccer Videos
髙橋 翔, 長谷山 美紀
映像情報メディア学会技術報告 = ITE technical report, Dec. 2016, Japanese - A Study on Detection of Similar Scenes based on Pass Regions in Soccer Videos
高橋翔, 長谷山美紀
映像情報メディア学会技術報告, 28 Nov. 2016, Japanese - 深層学習によって得られる画像特徴量を用いた道路構造物の点検データ検索の高精度化に関する検討
斉藤僚汰, 高橋翔, 小川貴弘, 長谷山美紀
電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 05 Nov. 2016, Japanese - 映像情報を用いた物体追跡技術の最前線とスポーツ科学への応用動向 6章 サッカー映像における試合内容の理解を促すデータの可視化
高橋翔, 長谷山美紀
映像情報メディア学会誌, 01 Sep. 2016, Japanese - Visualization Methods for Encourage Experience of Sports in Soccer Videos
高橋 翔, 長谷山 美紀
映像情報メディア学会誌 = The journal of the Institute of Image Information and Television Engineers, Sep. 2016, Japanese - 高速道路の維持管理における点検記録データ検索に対する技術者の評価を用いた検索精度向上に関する検討
高橋翔, 小川貴弘, 長谷山美紀
映像情報メディア学会年次大会講演予稿集(CD-ROM), 17 Aug. 2016, Japanese - A Note on Accurate Distress Classification for Maintenance Inspection of Road Structures : Integration of Multiple Classification Results based on Tag Data and Distress Images
前田 圭介, 高橋 翔, 小川 貴弘
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 22 Feb. 2016, Japanese - A Trial of Gaze Data Acquisition in Embankment Inspection of River Management
三改木 裕矢, 高橋 翔, 小川 貴弘
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 22 Feb. 2016, Japanese - A Note on Data Analysis for Supporting Distress Evaluation in Expressway Maintenance : Retrieval of Similar Inspection Records Using Distress Images
三改木 裕矢, 高橋 翔, 小川 貴弘
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 22 Feb. 2016, Japanese - A Note on Data Analysis for Supporting Distress Evaluation in Expressway Maintenance : Retrieval of Similar Inspection Records Using Distress Images
三改木 裕矢, 高橋 翔, 小川 貴弘
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 22 Feb. 2016, Japanese - A Trial of Gaze Data Acquisition in Embankment Inspection of River Management
三改木 裕矢, 高橋 翔, 小川 貴弘
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 22 Feb. 2016, Japanese - A Note on Accurate Distress Classification for Maintenance Inspection of Road Structures : Integration of Multiple Classification Results based on Tag Data and Distress Images
前田 圭介, 高橋 翔, 小川 貴弘
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 22 Feb. 2016, Japanese - A Note on Analysis of Gaze Data and Skill of Inspector in Embankment Inspection
高橋 翔, 三改木 裕矢, 小川 貴弘
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 22 Feb. 2016, Japanese - A Note on Data Analysis for Supporting Distress Evaluation in Expressway Maintenance : Retrieval of Similar Inspection Records Using Distress Images
三改木 裕矢, 高橋 翔, 小川 貴弘, 長谷山 美紀
映像情報メディア学会技術報告 = ITE technical report, 15 Feb. 2016, Japanese - A Trial of Gaze Data Acquisition in Embankment Inspection of River Management
三改木 裕矢, 高橋 翔, 小川 貴弘, 秋山 泰祐, 巖倉 啓子, 長谷山 美紀
映像情報メディア学会技術報告 = ITE technical report, 15 Feb. 2016, Japanese - A Note on Analysis of Gaze Data and Skill of Inspector in Embankment Inspection
高橋 翔, 三改木 裕矢, 小川 貴弘, 長谷山 美紀
映像情報メディア学会技術報告 = ITE technical report, 15 Feb. 2016, Japanese - A Note on Accurate Distress Classification for Maintenance Inspection of Road Structures : Integration of Multiple Classification Results based on Tag Data and Distress Images
前田 圭介, 高橋 翔, 小川 貴弘, 長谷山 美紀
映像情報メディア学会技術報告 = ITE technical report, 15 Feb. 2016, Japanese - A Study on High Performance Parallel Computing for Active Net-based Pass Region Estimation in Soccer Videos
TAKAHASHI Sho, HASEYAMA Miki
ITE Technical Report, 03 Dec. 2015, Japanese
This paper proposes a high performance parallel computing for Active net-based pass region estimation in soccer videos. In the soccer games, since the pass is very useful for analyses of various soccer tactics, the visualization of the pass regions is a very important task. Therefore, the pass region estimation method based on Active net is proposed. However, computation time of the pass region estimation must be reduced. Thus, in this paper, we propose a high performance parallel computing for Active net-based pass region estimation. By utilizing CUDA^as the computation environment, the high performance parallel computing is realized. - A Note on Estimation of Group Advantage for Group Tactics Analysis in Soccer Videos
TAKAHASHI Sho, HASEYAMA Miki
ITE Technical Report, 03 Dec. 2015, Japanese
This paper reports a effectiveness of the estimation method of group advantage in soccer videos. The group advantage represents the degree of team's superiority or inferiority in each group. For this analysis, the proposed method classifies players into some groups. As a result of this classification, the players in one group are closely related in terms of soccer tactics. In this method, the relationship between the players in the groups are analyzed by using player positions. Then, this method estimates group advantages by utilizing the relationship of the players. In the last of this paper, by utilizing the actual soccer videos, we evaluate the estimation method of the group advantage. - 道路構造物の変状画像に対する類似検索の高精度化に関する検討
高橋翔, 小川貴弘, 長谷山美紀
電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 07 Nov. 2015, Japanese - 個々の道路構造物に関する点検項目の導入による道路構造物の変状推定の高精度化に関する検討
前田圭介, 高橋翔, 小川貴弘, 長谷山美紀
電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 07 Nov. 2015, Japanese - A Note on Data Analysis for Maintenance Inspection of Infrastructures : Quantification of Relationship between Inspection Data Using Distress Images and Inspection Results
三改木 裕矢, 高橋 翔, 小川 貴弘
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 23 Feb. 2015, Japanese - A Note on Data Analysis for Maintenance Inspection of Infrastructures : Quantification of Relationship between Inspection Data Using Distress Images and Inspection Results
三改木 裕矢, 高橋 翔, 小川 貴弘
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 23 Feb. 2015, Japanese - A Note on Data Analysis for Maintenance Inspection of Infrastructures : Quantification of Relationship between Inspection Data Using Distress Images and Inspection Results
三改木 裕矢, 高橋 翔, 小川 貴弘
映像情報メディア学会技術報告 = ITE technical report, 16 Feb. 2015, Japanese - A Note on Network Analysis Based Detection of Important Player and Similar Scenes in Soccer Videos
TAKAHASHI Sho, HASEYAMA Miki
ITE Technical Report, 05 Dec. 2014, Japanese
This paper proposes a link analysis-based method for detecting important players and similar scenes in soccer videos. We define important players as follows: 1) the attacking player who have great relevancy to a score, 2) the defending player on the opposing team, and 3) players who assist the above players. Since soccer tactic analysis focuses not only on player skill but also relationships between players, this paper expresses the relationships between players as a network, which is constructed from player positions in the soccer video. The proposed method analyses the constructed network to detect important players and similar scenes. - 複数の画像特徴を用いたベイジアンネットワークに基づく構造物の変状の推定の高精度化に関する検討
前田圭介, 高橋翔, 小川貴弘, 長谷山美紀
電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 25 Oct. 2014, Japanese - 維持管理業務の効率化に向けた点検データの類似度算出における特徴選択に関する検討
三改木裕矢, 高橋翔, 小川貴弘, 長谷山美紀
電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 25 Oct. 2014, Japanese - A Note on Estimating Deformation Based on Bayesian Networks Using Images from Bridge Inspection
小林 克希, 高橋 翔, 小川 貴弘
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 17 Feb. 2014, Japanese - Definition of Soccer Player's Features Using Network Analysis and Its Application to Similarity Calculation between Players
岩井 和也, 高橋 翔, 小川 貴弘
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 17 Feb. 2014, Japanese - A Note on Estimating Deformation Based on Bayesian Networks Using Images from Bridge Inspection
小林 克希, 高橋 翔, 小川 貴弘
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 17 Feb. 2014, Japanese - Definition of Soccer Player's Features Using Network Analysis and Its Application to Similarity Calculation between Players
岩井 和也, 高橋 翔, 小川 貴弘
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 17 Feb. 2014, Japanese - A Note on Estimating Deformation Based on Bayesian Networks Using Images from Bridge Inspection
小林 克希, 高橋 翔, 小川 貴弘
映像情報メディア学会技術報告 = ITE technical report, 10 Feb. 2014, Japanese - Definition of Soccer Player's Features Using Network Analysis and Its Application to Similarity Calculation between Players
岩井 和也, 高橋 翔, 小川 貴弘
映像情報メディア学会技術報告 = ITE technical report, 10 Feb. 2014, Japanese - Bayesian network-based distress estimation using image features in road structure assessment
Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama
2014 IEEE 3rd Global Conference on Consumer Electronics, GCCE 2014, 03 Feb. 2014
© 2014 IEEE.This paper presents a Bayesian network-based method for estimating a distress of road structures from inspection data. The distress is represented by a damage of road structures and its degree. In the previous work, the distress was estimated by utilizing Bayesian network based on categories of road structures, details of road structures and damaged parts. However, inspection data include not only the above items but also images of the distress. Therefore, by introducing the use of the images to the previous work, improvement of the distress estimation accuracy can be expected. The proposed method calculates Bayesian network from inspection items and their corresponding images to perform the distress estimation. Experimental results show the effectiveness of the proposed method. - Adaptive parameter setting for pass region estimation in soccer videos and its performance verification
Sho Takahashi, Miki Haseyama
2013 IEEE 2nd Global Conference on Consumer Electronics, GCCE 2013, 01 Dec. 2013
This paper proposes an accurate pass region estimation method by introducing adaptive parameter settings. Our previous paper proposed a pass region estimation method by utilizing average values of ball and player velocities. However, such velocities vary according to player density and skill. Therefore, in order to realize a more accurate pass region estimation, the proposed method obtains parameters, which are ball and player velocities, from player positions in a target soccer video. By introducing the above parameter settings to pass region estimation, more realistic pass region can be obtained. Consequently, the accurate method of pass region estimation is realized. © 2013 IEEE. - ベイジアンネットワークを用いた構造物の点検データからの変状の推定
小林克希, 高橋翔, 小川貴弘, 長谷山美紀
電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 19 Oct. 2013, Japanese - Player Tracking by Using Level-Set Method in Soccer Video
TAKAHASHI Sho, LIM Wonkuk, HASEYAMA Miki
The IEICE transactions on information and systems (Japanese edetion), 01 Mar. 2013, Japanese
本論文では,サッカー映像からレベルセット法を用いて選手を追跡する手法を提案する.提案手法では,サッカー映像を各フレームが時間軸方向に重なるように連結した三次元データとして扱う.このデータに対して,レベルセット法を適用することで抽出される三次元の領域は,複数フレームに渡って存在する同一選手を包含する.提案手法では,この三次元の領域をサッカー映像から抽出することで,選手の追跡を実現する.したがって,提案手法では,フレームごとに選手を検出する必要がないため,フレームを個別に処理する従来手法における選手の検出と追跡それぞれの誤差によって精度が低下する問題を解決可能である.また,我々は,ユニフォームの色成分をサッカー映像から色コリログラムを用いて推定し,これをレベルセット法を用いて追跡する選手の特徴として導入する.これにより,提案手法では,追跡対象の特徴を事前に与えることなく,選手の頑健な追跡が可能となる.本文の最後では,実際にテレビで放送されたサッカー映像に対する実験により,提案手法の有効性を確認する. - A Note on Soccer Player Tracking Using Elastic Model : Performance Improvement Based on New Potential Energy
岩井 和也, 高橋 翔, 小川 貴弘
電子情報通信学会技術研究報告 : 信学技報, 18 Feb. 2013, Japanese - A Note on Accurate Estimation of Pitcher's Condition in Baseball Videos : Improvement of Features Based on Pitching Motions and Pitching Results
久保 純貴, 高橋 翔, 小川 貴弘
電子情報通信学会技術研究報告 : 信学技報, 18 Feb. 2013, Japanese - A Note on Accurate Soccer Video Segmentation Based on the Team Possessing the Ball
大貫 修平, 高橋 翔, 小川 貴弘
電子情報通信学会技術研究報告 : 信学技報, 18 Feb. 2013, Japanese - A Note on Soccer Player Tracking Using Elastic Model : Performance Improvement Based on New Potential Energy
岩井 和也, 高橋 翔, 小川 貴弘
電子情報通信学会技術研究報告 : 信学技報, 18 Feb. 2013, Japanese - A Note on Accurate Estimation of Pitcher's Condition in Baseball Videos : Improvement of Features Based on Pitching Motions and Pitching Results
久保 純貴, 高橋 翔, 小川 貴弘
電子情報通信学会技術研究報告 : 信学技報, 18 Feb. 2013, Japanese - A Note on Accurate Soccer Video Segmentation Based on the Team Possessing the Ball
大貫 修平, 高橋 翔, 小川 貴弘
電子情報通信学会技術研究報告 : 信学技報, 18 Feb. 2013, Japanese - A Study on an Accurate Method for Estimating Pass Region from Soccer Video : Definition of a New Evaluation Function Based on Changes in Player Position Geometry over Time
高橋 翔, 長谷山 美紀
電子情報通信学会技術研究報告 : 信学技報, 18 Feb. 2013, Japanese - A Study on an Accurate Method for Estimating Pass Region from Soccer Video : Definition of a New Evaluation Function Based on Changes in Player Position Geometry over Time
高橋 翔, 長谷山 美紀
電子情報通信学会技術研究報告 : 信学技報, 18 Feb. 2013, Japanese - A Note on Soccer Player Tracking Using Elastic Model : Performance Improvement Based on New Potential Energy
岩井 和也, 高橋 翔, 小川 貴弘
映像情報メディア学会技術報告 = ITE technical report, 11 Feb. 2013, Japanese - A Note on Accurate Estimation of Pitcher's Condition in Baseball Videos : Improvement of Features Based on Pitching Motions and Pitching Results
久保 純貴, 高橋 翔, 小川 貴弘
映像情報メディア学会技術報告 = ITE technical report, 11 Feb. 2013, Japanese - A Note on Accurate Soccer Video Segmentation Based on the Team Possessing the Ball
大貫 修平, 高橋 翔, 小川 貴弘
映像情報メディア学会技術報告 = ITE technical report, 11 Feb. 2013, Japanese - A Study on an Accurate Method for Estimating Pass Region from Soccer Video : Definition of a New Evaluation Function Based on Changes in Player Position Geometry over Time
高橋 翔, 長谷山 美紀
映像情報メディア学会技術報告 = ITE technical report, 11 Feb. 2013, Japanese - 8-3 A note on improvement of 3D pass region estimation method using player velocity in soccer videos
TAKAHASHI Sho, HASEYAMA Miki
ITE Winter Annual Convention, 18 Dec. 2012, Japanese
This paper realizes an improvement of 3D pass region estimation method by using player velocity in soccer videos. In the previous method, since the pass region was estimated regardless of player velocity, the accuracy was limited. Therefore, by introducing the player velocity to the pass region estimation, we improve the performance of the previous method. - 選手の移動速度を考慮したサッカー映像における3次元パス可能領域の推定に関する検討
高橋翔, 長谷山美紀
映像情報メディア学会冬季大会講演予稿集(CD-ROM), 27 Nov. 2012, Japanese - 弾性モデルを用いたサッカー映像における選手追跡の高精度化に関する検討
岩井和也, 高橋翔, 小川貴弘, 長谷山美紀
電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 20 Oct. 2012, Japanese - サッカーのチーム戦術推定手法を用いた試合映像の分割に関する検討
大貫修平, 高橋翔, 小川貴弘, 長谷山美紀
電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 20 Oct. 2012, Japanese - A Note on Estimation of Pitcher's Condition Based on Pitching Motion in Baseball Video and Scorebook
久保 純貴, 高橋 翔, 小川 貴弘
電子情報通信学会技術研究報告 : 信学技報, 20 Feb. 2012, Japanese - A Note on Estimation of Pitcher's Condition Based on Pitching Motion in Baseball Video and Scorebook
久保 純貴, 高橋 翔, 小川 貴弘
電子情報通信学会技術研究報告 : 信学技報, 20 Feb. 2012, Japanese - A method for detecting important events in soccer videos of amateur teams : An approach using tactical comments added to videos for soccer coaching
高橋 翔, 嶌田 聡, 長谷山 美紀
電子情報通信学会技術研究報告 : 信学技報, 20 Feb. 2012, Japanese - A method for detecting important events in soccer videos of amateur teams : An approach using tactical comments added to videos for soccer coaching
高橋 翔, 嶌田 聡, 長谷山 美紀
電子情報通信学会技術研究報告 : 信学技報, 20 Feb. 2012, Japanese - A Note on Estimation of Pitcher's Condition Based on Pitching Motion in Baseball Video and Scorebook
久保 純貴, 高橋 翔, 小川 貴弘
映像情報メディア学会技術報告, 13 Feb. 2012, Japanese - A method for detecting important events in soccer videos of amateur teams : An approach using tactical comments added to videos for soccer coaching
高橋 翔, 嶌田 聡, 長谷山 美紀
映像情報メディア学会技術報告, 13 Feb. 2012, Japanese - サッカー映像における選手位置抽出結果を用いたチーム戦術の推定に関する検討
大貫修平, 高橋翔, 小川貴弘, 長谷山美紀
電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 22 Oct. 2011, Japanese - 8-4 A note on detection of important events based on relationship between player action and sound on stadium in soccer videos
KUBO Junki, TAKAHASHI Sho, OGAWA Takahiro, HASEYAMA Miki
Proceedings of the ... ITE annual convention, 24 Aug. 2011, Japanese
This paper presents a detection method of important events based on relationship between player action and sound on stadium in soccer videos. Generally, since player action and sound on stadium have high correlation in the important events, we realize the detection by using their relationship based on canonical correlation analysis. - 8-5 A Note on Color Component Estimation of Team Uniforms in Soccer Videos based on Color Co-occurrence Histograms
TAKAHASHI Sho, HASEYAMA Miki
Proceedings of the ... ITE annual convention, 24 Aug. 2011, Japanese
This paper proposes a color estimation method of team uniforms in soccer videos based on color co-occurrence. The proposed method calculates color correlograms and selects sets of color components, whose co-occurrences are higher than the other sets. This enables the color component estimation of the team uniforms, which contain multiple colors. - 選手動作と歓声の関係性に注目したサッカー映像における重要場面の検出に関する検討
久保純貴, 高橋翔, 小川貴弘, 長谷山美紀
映像情報メディア学会年次大会講演予稿集(CD-ROM), 01 Aug. 2011, Japanese - 色の共起頻度を用いたサッカー映像におけるユニフォームの色成分の推定に関する検討
高橋翔, 長谷山美紀
映像情報メディア学会年次大会講演予稿集(CD-ROM), 01 Aug. 2011, Japanese - A Study on Accurate Pass Region Estimation in Soccer Videos-Introduction of Adaptive Parameter Settings-
高橋翔, 長谷山美紀
電子情報通信学会技術研究報告, 14 Feb. 2011, Japanese
In this paper, an accurate method of pass region estimation method is proposed by introduceing an adaptive parameter settings. We have proposed a pass region estimation method by utilizing average values of ball's velocity and player's velocity. However, velocities of a ball and players are different according to player's density and player's skill. Therefore, in the proposed method, parameters, which are a velocity of a ball and velocities of players, are set by using obtained player's positions from a target soccer video. Consicuently, the accurate method of pass region estimation is realized. - A Study on Accurate Pass Region Estimation in Soccer Videos : Introduction of Adaptive Parameter Settings
TAKAHASHI Sho, HASEYAMA Miki
ITE Technical Report, 14 Feb. 2011, Japanese
In this paper, an accurate method of pass region estimation method is proposed by introduceing an adaptive parameter settings. We have proposed a pass region estimation method by utilizing average values of ball's velocity and player's velocity. However, velocities of a ball and players are different according to player's density and player's skill. Therefore, in the proposed method, parameters, which are a velocity of a ball and velocities of players, are set by using obtained player's positions from a target soccer video. Consicuently, the accurate method of pass region estimation is real... - A Study on Accurate Pass Region Estimation in Soccer Videos : Introduction of Adaptive Parameter Settings
TAKAHASHI Sho, HASEYAMA Miki
IEICE technical report, 14 Feb. 2011, Japanese
In this paper, an accurate method of pass region estimation method is proposed by introduceing an adaptive parameter settings. We have proposed a pass region estimation method by utilizing average values of ball's velocity and player's velocity. However, velocities of a ball and players are different according to player's density and player's skill. Therefore, in the proposed method, parameters, which are a velocity of a ball and velocities of players, are set by using obtained player's positions from a target soccer video. Consicuently, the accurate method of pass region estimation is real... - 8-4 A note on detection of important events based on relationship between player action and sound on stadium in soccer videos
KUBO Junki, TAKAHASHI Sho, OGAWA Takahiro, HASEYAMA Miki
PROCEEDINGS OF THE ITE ANNUAL CONVENTION, 2011, Japanese
This paper presents a detection method of important events based on relationship between player action and sound on stadium in soccer videos. Generally, since player action and sound on stadium have high correlation in the important events, we realize the detection by using their relationship based on canonical correlation analysis. - 8-5 A Note on Color Component Estimation of Team Uniforms in Soccer Videos based on Color Co-occurrence Histograms
TAKAHASHI Sho, HASEYAMA Miki
PROCEEDINGS OF THE ITE ANNUAL CONVENTION, 2011, Japanese
This paper proposes a color estimation method of team uniforms in soccer videos based on color co-occurrence. The proposed method calculates color correlograms and selects sets of color components, whose co-occurrences are higher than the other sets. This enables the color component estimation of the team uniforms, which contain multiple colors. - A Note on 3D Active Grid Based Estimation of 3D Pass Region from Broadcasted Soccer Videos
高橋翔, 長谷山美紀
映像情報メディア学会技術報告, 15 Feb. 2010, Japanese
This paper proposes an estimation method of 3D pass regions from the actual broadcasted soccer videos, where the 3D pass region has a high probability in which the pass succeeds. We have proposed an estimation method of 2D pass regions by using player positions and a ball position, where the player positions and the ball position are obtained as 2D coordinate from the actual broadcasted soccer video. However, the pass regions exist on a 3D space as a region of a 3D shape. Therefore, the proposed method realizes the estimation of the 3D pass region from the 3D space by using the 3D Active Grid. In order to use the 3D Active Grid, new volume data are generated by using player and ball positions, where the volume data indicate a possibiliy in which players can reach positions in the 3D space. Consequently, this paper realizes the estimation of the pass regions by using the 3D Active Grid. - A Note on 3D Active Grid Based Estimation of 3D Pass Region from Broadcasted Soccer Videos
TAKAHASHI Sho, HASEYAMA Miki
IEICE technical report. Image engineering, 08 Feb. 2010, Japanese
This paper proposes an estimation method of 3D pass regions from the actual broadcasted soccer videos, where the 3D pass region has a high probability in which the pass succeeds. We have proposed an estimation method of 2D pass regions by using player positions and a ball position, where the player positions and the ball position are obtained as 2D coordinate from the actual broadcasted soccer video. However, the pass regions exist on a 3D space as a region of a 3D shape. Therefore, the proposed method realizes the estimation of the 3D pass region from the 3D space by using the 3D Active Gr... - A Note on 3D Active Grid Based Estimation of 3D Pass Region from Broadcasted Soccer Videos
TAKAHASHI Sho, HASEYAMA Miki
IEICE technical report, 08 Feb. 2010, Japanese
This paper proposes an estimation method of 3D pass regions from the actual broadcasted soccer videos, where the 3D pass region has a high probability in which the pass succeeds. We have proposed an estimation method of 2D pass regions by using player positions and a ball position, where the player positions and the ball position are obtained as 2D coordinate from the actual broadcasted soccer video. However, the pass regions exist on a 3D space as a region of a 3D shape. Therefore, the proposed method realizes the estimation of the 3D pass region from the 3D space by using the 3D Active Gr... - PLAYERS TRACKING APPROACH USING LEVEL-SET METHOD BASED ON COLOR COMPONENTS OF PLAYERS IN SOCCER VIDEOS
TAKAHASHI Sho, LIM Wonkuk, HASEYAMA Miki
画像符号化シンポジウム資料, 2010, English - アクティブグリッドを用いたサッカー映像におけるパス可能領域の推定に関する検討
高橋翔, 長谷山美紀
電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM), 17 Oct. 2009, Japanese
Courses
- Multi-dimensional Signal Processing Theory for Applications
Hokkaido University
Dec. 2020 - Present - Infrastructure Planning
Hokkaido University
Oct. 2019 - Present - Exercise in Infrastructure Planning
Hokkaido University
Apr. 2019 - Present - Introduction to Informatics I
Hokkaido University
2020 - 2020 - Field Training of Surveying
Hokkaido University
Apr. 2019 - Sep. 2019 - 計算機演習
北海学園大学
Apr. 2009 - Mar. 2011
Affiliated academic society
Research Themes
- Monitoring of Road Traffic Systems under Information Acquisition Constraints in Times of Disasters
Grants-in-Aid for Scientific Research
01 Apr. 2023 - 31 Mar. 2026
杉浦 聡志, 高橋 翔, 倉内 文孝, 中西 航
Japan Society for the Promotion of Science, Grant-in-Aid for Scientific Research (B), Hokkaido University, 23H01521 - A Construction of a Real-time Digital Twin in Snow and Cold Regions and Study of Disaster Prevention Systems
Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (B)
01 Apr. 2022 - 31 Mar. 2026
高橋 翔, 杉浦 聡志, 萩原 亨
Japan Society for the Promotion of Science, Grant-in-Aid for Scientific Research (B), Hokkaido University, 22H01607 - デジタルツインによる冬期道路交通マネジメントシステムの技術開発
道路政策の質の向上に資する技術研究開発
Apr. 2023 - Mar. 2026
髙橋翔, 萩原亨, 有村幹治, 浅田拓海, 永田泰浩, 大井元揮, 芝崎拓, 小西信義, 丹治和博, 小松麻美, 槌本陽, 山本郁淳, 内藤利幸, 松田真宜, 高橋歩夢
国土交通省, 本格研究, 新道路技術会議, Principal investigator - 冬期の自動運転を支援する道路管理システムに関する研究
科学研究費助成事業 基盤研究(B)
01 Apr. 2019 - 31 Mar. 2023
萩原 亨, 宗廣 一徳, 高橋 翔, 有村 幹治
本研究では交通シミュレーションソフトの VISSIMを用いて、冬期路面を想定したACC制御車の混在が低交通量の交通流に与える影響について明らかにする。最初に、ACC制御車の走行をVISSIMで再現する追従モデルを開発した。次に、フィールド実験におけるACC制御車(追従車)の追従挙動を用いてVISSIMで再現したACC制御車の追従モデルの妥当性を検証した。これらの結果をベースに、冬期路面を想定した長い設定車間時間の影響を検討した。交通流シミュレーションの結果から、ACC制御車の混在率が高く、設定車間時間が長いとき、平均速度・平均旅行時間・平均遅れ時間に大きな影響はない結果となった。ただし、ACC制御車の混在率が高く時間交通量が多い条件で、設定車間時間を長くすると平均遅れ時間が長くなるなど、交通流へ影響する結果となった。
日本学術振興会, 基盤研究(B), 北海道大学, 19H02254 - 冬期の自動運転を支援する道路管理システムに関する研究
科学研究費補助金(基盤研究(B))
Apr. 2019 - Mar. 2023
萩原 亨
文部科学省, Competitive research funding - Super-MultiModal Human Analysis Platform for Next Generation of Advanced Retrieval
Grants-in-Aid for Scientific Research
01 Apr. 2017 - 31 Mar. 2022
Haseyama Miki
We constructed a super-multimodal human analysis infrastructure to realize the next-generation retrieval technology that can accurately estimate users’ interests through sensory data. In this research, we have succeeded in constructing the fundamental technology that was the goal of our research, and conducted demonstration experiments to verify the effectiveness of our technology. Specifically, we constructed an information retrieval and recommendation system based on the super-multimodal human analysis platform and verified the effectiveness of the technology for tourists in the digital signage space in Sapporo City. In summary, this research has contributed to the formation of fundamental technology in the field of multimedia search and recommendation by establishing a super-multimodal human analysis infrastructure and demonstrating its effectiveness.
Japan Society for the Promotion of Science, Grant-in-Aid for Scientific Research (B), Hokkaido University, 17H01744 - 次世代高精度検索を実現するスーパーマルチモーダル人間情報解析基盤
科学研究費補助金(基盤研究(B))
Apr. 2017 - Mar. 2022
長谷山 美紀
文部科学省, Competitive research funding - A study on development of visualization techniques for indicating various sports contents under various environments and users
Grants-in-Aid for Scientific Research
01 Apr. 2017 - 31 Mar. 2021
Takahashi Sho
The formation of players is a very important element in tactics of field sports such as soccer, rugby football, and baseball, etc. These tactics are expressed by communicating with multiple players on the field. Thus, the analysis methods for the formation of players are necessary for understanding tactics of sports contents. Therefore, in this project, we constructed some advanced analysis methods for understanding tactics of sports contents based on the players' formation, and some visualization techniques which realize dynamic data indication with user’s skill and interest. The indicated data are players’ position, information of each team, a situation of the game, and tactics.
Japan Society for the Promotion of Science, Grant-in-Aid for Scientific Research (C), Hokkaido University, 17K00148 - 自治体による観光情報発信支援のためのサイバーフィジカルデータ解析プラットフォームに関する研究開発
Strategic Information and Communication R&D Promotion Programme
Jun. 2018 - Mar. 2021
Miki Haseyama
Ministry of International Affairs and Communications, Competitive research funding - 環境や利用者に適応して多様なスポーツのコンテンツを提示する次世代可視化技術の構築
科学研究費補助金(基盤研究(C))
Apr. 2017 - Mar. 2021
高橋 翔
文部科学省, Principal investigator, Competitive research funding - A Study on Adaptive Data Visualization for Sports Video Contents based on Individual Experience and Knowledge
Grants-in-Aid for Scientific Research Grant-in-Aid for Young Scientists (B)
01 Apr. 2014 - 31 Mar. 2018
Takahashi Sho
In this research, in order to construct a system that presents useful data for the audience of sports, based on user experience and knowledge, we studied the adaptive visualization method of pass course and automatically generated live comments, etc. The proposed method analyzed the relationship between the multimedia contents that are broadcast videos, live character data on the Internet etc., and the operation history by the user.
Japan Society for the Promotion of Science, Grant-in-Aid for Young Scientists (B), Hokkaido University, Principal investigator, Competitive research funding, 26730057 - 映像の意味理解を実現する映像解析手法の確立とその応用に関する研究
科学研究費補助金(特別研究奨励費)
Apr. 2011 - Mar. 2013
高橋 翔
文部科学省, Principal investigator, Competitive research funding - 映像の意味理解を実現する映像解析手法の確立とその応用に関する研究
科学研究費助成事業 特別研究員奨励費
2011 - 2012
高橋 翔
サッカー映像や野球映像などのスポーツ映像は世界中の人々が関心を持ち,非常に多くの視聴者が存在する.さらに,スポーツ映像はプロやアマチュアを問わずスポーツ教育へ利用されており,非常に重要な映像資料として扱われている.しかしながら,それらのスポーツ映像を視聴者が十分に理解するためには,選手や戦術などに関する知識や経験が要求され,視聴者が映像を視聴可能な時間は限られている.このため,映像を効果的に視聴し,内容を理解することを可能とする技術が必要とされている,そこで,申請者は映像を効果的に視聴可能とする技術の確立のために「高レベル特徴量を用いた映像意味理解に関する映像解析」および「映像解析手法のスポーツ教育への応用」について研究を進めた.
平成24年度は,平成23年度において計画を達成することにより確立された映像意味理解に関する映像解析手法を用い,選手及びチームの技術向上や新たな技術の獲得を目的としたスポーツ教育への応用についての検討を行った,具体的には,平成23年度に実現された類似場面検索を行うことでテレビ放送や個人で撮影された大量のスポーツ映像の中から参考となるプレーや議論の対象となる場面の検索が可能となる手法を提案した.また,平成23年度の成果に基づき,擬似的な試合を効果的にシミュレーションすることを可能とした.以上のように,平成24年度は,映像意味理解に関する映像解析手法のスポーツ教育への応用についての検討を進めた.
日本学術振興会, 特別研究員奨励費, 北海道大学, 11J01938 - 深層学習によるAI機構を有するARを用いたデータ提示の基礎システム構築
研究助成金
高橋 翔
戸田育英財団, Principal investigator, Competitive research funding
Industrial Property Rights
- 路面状態判定装置、路面状態判定システム、車両、路面状態判定方法、及びプログラム
Patent right, 岩崎悠志, 高橋翔, 萩原亨, 大廣智則, 株式会社ブリヂストン, 株式会社ネクスコ・エンジニアリング北海道
特願2021-088688, 26 May 2021
特開2022-181641, 08 Dec. 2022 - 路面状態判定装置、路面状態判定システム、車両、路面状態判定方法、及びプログラム
Patent right, 岩崎悠志, 高橋翔, 萩原亨, 大廣智則, 株式会社ブリヂストン, 株式会社ネクスコ・エンジニアリング北海道
2021-088683, 26 May 2021
特開2022-181640, 08 Dec. 2022 - 体験記録システム、体験記録方法および体験記録プログラム
Patent right, 嶌田 聡, 東野 豪, 長谷山 美紀, 高橋 翔, 日本電信電話株式会社, 国立大学法人北海道大学
特願2012-277957, 20 Dec. 2012
特開2014-123817, 03 Jul. 2014
特許第5920785号
22 Apr. 2016
201603007762337580 - 映像アノテーション付与装置およびその動作方法
Patent right, 嶌田 聡, 長谷山 美紀, 高橋 翔, 日本電信電話株式会社, 国立大学法人北海道大学
特願2011-152899, 11 Jul. 2011
特開2013-021482, 31 Jan. 2013
201303058263892263