Advancing Monocular Video-Based Gait Analysis Using Motion Imitation with Physics-Based Simulation

arXiv:2402.12676v1 Announce Type: new
Abstract: Gait analysis from videos obtained from a smartphone would open up many clinical opportunities for detecting and quantifying gait impairments. However, existing approaches for estimating gait parameters from videos can produce physically implausible results. To overcome this, we train a policy using reinforcement learning to control a physics simulation of human movement to replicate the movement seen in video. This forces the inferred movements to be physically plausible, while improving the accuracy of the inferred …

abstract analysis arxiv clinical cs.cv opportunities parameters physics policy reinforcement reinforcement learning simulation smartphone train type video videos