Author:
Evans Murray,Colyer Steffi,Salo Aki,Cosker Darren
Abstract
AbstractMaking accurate measurements of human body motions using only passive, non-interfering sensors such as video is a difficult task with a wide range of applications throughout biomechanics, health, sports and entertainment. The rise of machine learning-based human pose estimation has allowed for impressive performance gains, but machine learning-based systems require large datasets which might not be practical for niche applications. As such, it may be necessary to adapt systems trained for more general-purpose goals, but this might require a sacrifice in accuracy when compared with systems specifically developed for the application. This paper proposes two approaches to measuring a sprinter’s foot-ground contact locations and timing (step length and step frequency), a task which requires high accuracy. The first approach is a learning-free system based on occupancy maps. The second approach is a multi-camera 3D fusion of a state-of-the-art machine learning-based human pose estimation model. Both systems use the same underlying multi-camera system. The experiments show the learning-free computer vision algorithm to provide foot timing to better than 1 frame at 180 fps, and step length accurate to 7 mm, while the system based on pose estimation achieves timing better than 1.5 frames at 180 fps, and step length estimates accurate to 20 mm.
Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,Computer Vision and Pattern Recognition,Hardware and Architecture,Software
Reference57 articles.
1. Allison, T.: More than a man in a monkey suit: andy serkis, motion capture, and digital realism. Q Rev Film Video 28(4), 325–341 (2011). https://doi.org/10.1080/10509208.2010.500947
2. Amini, A., Banitsas, K., Hosseinzadeh, S.: A new technique for foot-off and foot contact detection in a gait cycle based on the knee joint angle using microsoft kinect v2. In: 2017 IEEE EMBS International Conference on Biomedical Health Informatics (BHI), pp. 153–156 (2017). https://doi.org/10.1109/BHI.2017.7897228
3. Bezodis, I., Salo, A.I.T., Kerwin, D.: A longitudinal case study of step characteristics in a world class sprint athlete. In: Proceedings of XXVI International Conference on Biomechanics in Sports, pp. 537–540 (2008)
4. Bezodis, I., Thomson, A., Gittoes, M., Kerwin, D.: Identification of instants of touchdown and take-off in sprint running using and automatic motion analysis system. In: 25th International Symposium on Biomechanics in sports, pp. 501–504 (2007)
5. Bezodis, N.E., Salo, A.I.T., Trewartha, G.: Relationships between lower-limb kinematics and block phase performance in a cross section of sprinters. Eur. J. Sport Sci. 15(2), 118–124 (2015)
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献