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Skeleton is a winter sport where performance is greatly affected by the velocity an athlete can achieve during their start up to the point where they load themselves onto their sled. As such, it is of interest to athletes and coaching staff to be able to monitor the performance of their athletes and how they respond to different training schedules and techniques. This paper proposes a non-invasive vision based method for measuring the velocity of a skeleton athlete and their sled during the push start. Mean differences in estimated velocity between ground truth data and our proposed system were -0.005 (+/- 0.186) m/s for the athlete mass centre and -0.017 (+/- 0.133) m/s for the sled. The results compare favourably to techniques previously presented in the biomechanics and sport science literature.
|Publication status||Published - 16 Jun 2020|
|Event||IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2020 - The Washington State Convention Center, Seattle, USA United States|
Duration: 16 Jun 2020 → 18 Jun 2020
|Conference||IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2020|
|Abbreviated title||CVPR 2020|
|Country/Territory||USA United States|
|Period||16/06/20 → 18/06/20|
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- 1 Finished
1/09/15 → 28/02/21
Project: Research council