Abstract
Estimation of human energy expenditure in sports and exercise contributes to performance analyses and tracking of physical activity levels. The focus of this work is to develop a video-based method for estimation of energy expenditure in athletes. We propose a method using thermal video analysis to automatically extract the cyclic motion pattern, in walking and running represented as steps, and analyse the frequency. Experiments are performed with one subject in two different tests, each at 5, 8, 10, and 12 km/h. The results of our proposed video-based method is compared to concurrent measurements of oxygen uptake. These initial experiments indicate a correlation between estimated step frequency and oxygen uptake. Based on the preliminary results we conclude that the proposed method has potential as a future non-invasive approach to estimate energy expenditure during sports.
| Original language | English |
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| Title of host publication | Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) |
| Publisher | IEEE |
| Publication date | 24 Aug 2017 |
| ISBN (Print) | 978-1-5386-0734-3 |
| ISBN (Electronic) | 978-1-5386-0733-6 |
| DOIs | |
| Publication status | Published - 24 Aug 2017 |
| Event | 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) - Honolulu, United States Duration: 21 Jul 2017 → 26 Jul 2017 http://cvpr2017.thecvf.com/ |
Conference
| Conference | 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) |
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| Country/Territory | United States |
| City | Honolulu |
| Period | 21/07/2017 → 26/07/2017 |
| Internet address |