Real-Time Markerless Human Body Tracking with Multi-View 3-D Voxel Reconstruction

We present an approach to full human-body tracking, using markerless multiview images as input, performing acquisition, reconstruction and tracking in real-time on a single PC. Our approach employs a hierarchical visual-hull algorithm which segments only the most interesting regions of the images and includes colour information. The tracking step uses blobs attached to a kinematic model to recover joint angles in an expectation-maximization framework. We demonstrate the robustness of the approach on video sequences of various body configurations in an unaugmented office environment. We also show that tracking challenging poses with self-occlusions is possible without the processing cost of stochastic sampling schemes.