AI RESEARCH
Markerless Motion Capture for Biomechanical Whole-Body Kinematic Estimation in Infants
arXiv CS.CV
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ArXi:2605.17120v1 Announce Type: new arly identification of motor impairment in infancy relies on expert visual assessment of spontaneous movement, motivating the development of automated, objective alternatives. One promising approach is using computer vision, which benefits from high quality pose estimation from video. In this study, we systematically evaluated three state-of-the-art pose estimation frameworks (MeTRAbs-ACAE, SAM 3D Body, and Sapiens) on 100 videos over 13 sessions of 8 infants recorded with a multi-view markerless motion capture system.