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AI analyzes tennis biomechanics from video with high accuracy

Researchers have developed a multi-task pipeline for analyzing tennis stroke biomechanics using only RGB video. The system automatically identifies strokes and predicts shot direction and posture quality, offering coaching tips based on a rule-based feedback layer. Utilizing MediaPipe Pose for landmark detection and a custom transformer model called TennisTransformerGPU, the pipeline achieves high accuracy in stroke-type recognition, even when trained on professional players and evaluated on amateurs. The study highlights the critical importance of using metric world coordinates for accurate cross-player analysis. AI

RANK_REASON Academic paper detailing a novel AI application for sports biomechanics analysis. [lever_c_demoted from research: ic=1 ai=1.0]

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  1. arXiv cs.CV TIER_1 English(EN) · Jigyashman Hazarika ·

    Multi-Task Tennis Stroke Biomechanics Analysis Using MediaPipe Pose

    arXiv:2606.15992v1 Announce Type: new Abstract: We built a multi-task pipeline for tennis stroke biomechanics from plain RGB video. On top of pose-based stroke recognition, it adds two new tasks, predicting shot direction and grading posture quality, plus a rule-based feedback la…