Evaluation of Machine Learning based Pose Estimation of Surfers on River Waves
Abstract
In this work we are describing our preliminary experimental evaluation of open-source machine learning based pose estimation solutions for tracking a surfer’s skeleton on a stationary wave. We are briefly describing the sport’s environment and development and the current state-of-the-art of machine learning based single camera 2D and 3D pose estimation solutions. The main part of the paper deals with the experiment’s setup and the interpretation of the resulting data of the movements of one surfer. We are closing with our lessons learned and our next steps.
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| Titel | Evaluation of Machine Learning based Pose Estimation of Surfers on River Waves |
|---|---|
| Medien | PETRA '23: Proceedings of the 16th International Conference on PErvasive Technologies Related to Assistive Environments |
| Verlag | ACM |
| Heft | --- |
| Band | 2023 |
| ISBN | --- |
| Verfasser/Herausgeber | Prof. Michael Zöllner, Stefan Kniesburges, Moritz Krause, Michael Döllinger, Jan Gemeinhardt |
| Seiten | --- |
| Veröffentlichungsdatum | 01.07.2023 |
| Projekttitel | --- |
| Zitation | Zöllner, Michael; Kniesburges, Stefan; Krause, Moritz; Döllinger, Michael; Gemeinhardt, Jan (2023): Evaluation of Machine Learning based Pose Estimation of Surfers on River Waves. PETRA '23: Proceedings of the 16th International Conference on PErvasive Technologies Related to Assistive Environments 2023. DOI: 10.1145/3594806 |