Model-based markerless human motion capture from multiple camera sequences - Zhang, Zheng. (2013)
The tracking of 3D articulated body motion from video sequences, or markerless motion capture, plays an important role in a wide variety of potential applications: human computer interaction, biomechanics, computer animation, surveillance and sport analysis. Though there have been remarkable advances in vision-based motion capture, pose tracking from multiple images has not been extensively studied: no existing work produces a solution comparable to that of existing marker-based motion capture methods which generally can recover accurate 3D full body motions in real-time. In this thesis, we develop new methods for human body motion tracking with the main focus on tackling the scenarios where multiple cameras are assumed available. Our research follows a 3D data-based tracking framework, where 3D data, e.g., colored volume and scene flow (i.e., 3D optical flow), is firstly reconstructed and then the optimal human posture is recovered from the 3D data at every instant in time. A multiple camera system with eight cameras is firstly assembled to capture synchronized multiple image video streams. We present and implement efficient methods for synthesizing and rendering 3D reconstruction of the real world dynamic scenes.