Markerless Mocap

This project develops a markerless motion capture system to serve as ground truth for real-time finger joint angle prediction from surface electromyography (sEMG) signals, enabling affordable hand motion analysis with applications in prosthetics and rehabilitation.I built the computer vision pipeline using MediaPipe to extract and compute individual finger joint angles from RGB camera input