Evaluating current state of monocular 3D pose models for golf
DOI:
https://doi.org/10.7557/18.6793Keywords:
Human pose estimation, smpl, sport, 3D pose, 2D pose, kinematic analysisAbstract
Monocular 3D human pose estimation has reached an impressive performance. State-of-the-art mod- els predict joint locations that can be accurately reprojected back into the image, resulting in vi- sually convincing detections. However, our aim is to use the predicted poses in a domain with high- frequency movements, that is, for video of ath- letes performing golf swings. Our investigation is based on accurate marker-based motion capture data. Also, for our data, the predicted 3D joint locations look convincing when we reproject them into the image. However, by quantitatively com- paring the results with the motion capture data, we see significant model errors that are too erroneous to be used for any kinematic analysis of the move- ments. Thus we conclude that the current models cannot be used out of the box for advanced golf analytics.
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