Hammer throw distance estimation using deep learning and physics-based modeling

doi:10.1016/j.eswa.2026.132022

Hammer throw distance estimation using deep learning and physics-based modeling

2026-03-11

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DOI：10.1016/j.eswa.2026.132022

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• Novel deep learning and physics-based hammer throw distance estimation framework • We use multi-view synchronized videos to reconstruct 3D hammer trajectory • We calculate hammer throw release parameters using equations of motion • We achieve an average error of less than three meters, corresponding to 4 • Framework supports athletes’ indoor training where real distances cannot be measured

Keywords:

Deep learning

Sports performance evaluation

Biomechanics

Hammer throw analytics

Hammer throw distance estimation using deep learning and physics-based modeling

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