3D Motion Capture from 2D Video

3D motion capture from 2D video technology uses computer vision and machine learning to extract three-dimensional motion data from standard two-dimensional video recordings. This eliminates the need for expensive multi-camera motion capture studios, specialized markers, or complex sensor arrays traditionally required for accurate motion tracking.

The technology employs deep learning models trained to understand human biomechanics and infer 3D pose and movement from 2D video frames. By analyzing body proportions, joint relationships, and movement patterns, the system reconstructs accurate 3D motion data. This extracted motion can then be converted into robot control commands, enabling teleoperation where human movements are translated to robotic actions. Applications include robot training, animation, sports analysis, rehabilitation monitoring, and human-robot collaboration systems. The approach dramatically reduces the cost and complexity of motion capture while making it accessible from any standard video recording.