Voxel based annealed particle filtering for markerless 3D articulated motion capture

This paper presents a view-independent approach to markerless hu-man motion capture in low resolution sequences from multiple cal-ibrated and synchronized cameras. Redundancy among cameras is exploited to generate a 3D voxelized representation of the scene and a human body model (HBM) is introduced towards analyzing these data. An annealed particle filtering scheme where every particle encodes an instance of the pose of the HBM is employed. Likeli-hood between particles and input data is performed using occupancy and surface information and kinematic constrains are imposed in the propagation step towards avoiding impossible poses. Test over the HumanEva annotated dataset yield quantitative results showing the effectiveness of the proposed algorithm. Index Terms — Human motion capture, multi-camera analysis, particle filtering, voxel processin