Resumé

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.
OriginalsprogEngelsk
TitelProceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
ForlagIEEE
Publikationsdato24 aug. 2017
ISBN (Trykt)978-1-5386-0734-3
ISBN (Elektronisk)978-1-5386-0733-6
DOI
StatusUdgivet - 24 aug. 2017
Begivenhed2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) - Honolulu, USA
Varighed: 21 jul. 201726 jul. 2017
http://cvpr2017.thecvf.com/

Konference

Konference2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
LandUSA
ByHonolulu
Periode21/07/201726/07/2017
Internetadresse

Fingerprint

Sports
Oxygen
Experiments
Energy Metabolism
Hot Temperature

Citer dette

Gade, R., Larsen, R. G., & Moeslund, T. B. (2017). Measuring energy expenditure in sports by thermal video analysis. I Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) IEEE. https://doi.org/10.1109/CVPRW.2017.29
Gade, Rikke ; Larsen, Ryan Godsk ; Moeslund, Thomas B. / Measuring energy expenditure in sports by thermal video analysis. Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE, 2017.
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title = "Measuring energy expenditure in sports by thermal video analysis",
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.",
author = "Rikke Gade and Larsen, {Ryan Godsk} and Moeslund, {Thomas B.}",
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Gade, R, Larsen, RG & Moeslund, TB 2017, Measuring energy expenditure in sports by thermal video analysis. i Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Honolulu, USA, 21/07/2017. https://doi.org/10.1109/CVPRW.2017.29

Measuring energy expenditure in sports by thermal video analysis. / Gade, Rikke; Larsen, Ryan Godsk; Moeslund, Thomas B.

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE, 2017.

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

TY - GEN

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AU - Moeslund, Thomas B.

PY - 2017/8/24

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N2 - 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.

AB - 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.

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Gade R, Larsen RG, Moeslund TB. Measuring energy expenditure in sports by thermal video analysis. I Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE. 2017 https://doi.org/10.1109/CVPRW.2017.29