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https://github.com/cepdnaclk/e15-4yp-sports-action-recognition

This includes a novel method to measure the quality of the actions performed in Olympic weightlifting using human action recognition in videos. Human action recognition is a well-studied problem in computer vision and on the other hand action quality assessment is researched and experimented comparatively low. This is due to the lack of datasets that can be used to assess the quality of actions. In this research, we introduce a method to assess player techniques in weightlifting by using skeleton-based human action recognition. Furthermore, we introduce a new video dataset for action recognition in weightlifting which is annotated to frame level. We intended to develop a viable automated scoring system through action recognition that would be beneficial in the sports industry.
https://github.com/cepdnaclk/e15-4yp-sports-action-recognition

action-quality-assessment computer-vision final-year-project human-action-recognition openpose vision

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This includes a novel method to measure the quality of the actions performed in Olympic weightlifting using human action recognition in videos. Human action recognition is a well-studied problem in computer vision and on the other hand action quality assessment is researched and experimented comparatively low. This is due to the lack of datasets that can be used to assess the quality of actions. In this research, we introduce a method to assess player techniques in weightlifting by using skeleton-based human action recognition. Furthermore, we introduce a new video dataset for action recognition in weightlifting which is annotated to frame level. We intended to develop a viable automated scoring system through action recognition that would be beneficial in the sports industry.

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