A Systematic Review of the Application of Camera-Based Human Pose Estimation in the Field of Sport and Physical Exercise

被引:39
作者
Badiola-Bengoa, Aritz [1 ]
Mendez-Zorrilla, Amaia [1 ]
机构
[1] Univ Deusto, eVida Res Grp, Bilbao 48007, Spain
关键词
human pose estimation; sport; physical exercise; human joint estimation; keypoint detection;
D O I
10.3390/s21185996
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Human Pose Estimation (HPE) has received considerable attention during the past years, improving its performance thanks to the use of Deep Learning, and introducing new interesting uses, such as its application in Sport and Physical Exercise (SPE). The aim of this systematic review is to analyze the literature related to the application of HPE in SPE, the available data, methods, performance, opportunities, and challenges. One reviewer applied different inclusion and exclusion criteria, as well as quality metrics, to perform the paper filtering through the paper databases. The Association for Computing Machinery Digital Library, Web of Science, and dblp included more than 500 related papers after the initial filtering, finally resulting in 20. In addition, research was carried out regarding the publicly available data related to this topic. It can be concluded that even if related public data can be found, much more data is needed to be able to obtain good performance in different contexts. In relation with the methods of the authors, the use of general purpose systems as base, such as Openpose, combined with other methods and adaptations to the specific use case can be found. Finally, the limitations, opportunities, and challenges are presented.
引用
收藏
页数:25
相关论文
共 70 条
[1]   PoseTrack: A Benchmark for Human Pose Estimation and Tracking [J].
Andriluka, Mykhaylo ;
Iqbal, Umar ;
Insafutdinov, Eldar ;
Pishchulin, Leonid ;
Milan, Anton ;
Gall, Juergen ;
Schiele, Bernt .
2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2018, :5167-5176
[2]   2D Human Pose Estimation: New Benchmark and State of the Art Analysis [J].
Andriluka, Mykhaylo ;
Pishchulin, Leonid ;
Gehler, Peter ;
Schiele, Bernt .
2014 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2014, :3686-3693
[3]  
[Anonymous], 2010, bmvc
[4]   A Deep Learning and Computer Vision Based Multi-Player Tracker for Squash [J].
Baclig, Maria Martine ;
Ergezinger, Noah ;
Mei, Qipei ;
Gul, Mustafa ;
Adeeb, Samer ;
Westover, Lindsey .
APPLIED SCIENCES-BASEL, 2020, 10 (24)
[5]   Functional Data Analysis of Rowing Technique Using Motion Capture Data [J].
Becker, Artur ;
Herrebroden, Henrik ;
Sanchez, Victor E. Gonzalez ;
Nymoen, Kristian ;
Dal Sasso Freitas, Carla Maria ;
Torresen, Jim ;
Jensenius, Alexander Refsum .
PROCEEDINGS OF THE 6TH INTERNATIONAL CONFERENCE ON MOVEMENT AND COMPUTING MOCO'19, 2019,
[6]  
Burenius M., 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), P1634, DOI 10.1109/ICCVW.2011.6130445
[7]   Temporal Hockey Action Recognition via Pose and Optical Flows [J].
Cai, Zixi ;
Neher, Helmut ;
Vats, Kanav ;
Clausi, David A. ;
Zelek, John .
2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW 2019), 2019, :2543-2552
[8]  
Cao Z., 2016, ABS161108050 CORR
[9]   OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields [J].
Cao, Zhe ;
Hidalgo, Gines ;
Simon, Tomas ;
Wei, Shih-En ;
Sheikh, Yaser .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2021, 43 (01) :172-186
[10]   Cascaded Pyramid Network for Multi-Person Pose Estimation [J].
Chen, Yilun ;
Wang, Zhicheng ;
Peng, Yuxiang ;
Zhang, Zhiqiang ;
Yu, Gang ;
Sun, Jian .
2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2018, :7103-7112