A Multi-camera Network System for Markerless 3D Human Body Voxel Reconstruction

This paper presents a fully automated system for realtime 3D human visual hull reconstruction and skeleton voxels extraction. The main contributions include: (1) A novel network based system is presented, which uses AXIS network cameras as video capture device, and performs a parallel processing among data capture, 3D voxel reconstruction and display. (2) A new human visual hull reconstruction algorithm is given. This approach firstly segments the foreground accurately by an efficient Gaussian Mixture Model (GMM) and a shadow model in HSV color space, then extends the standard Shape-From-Silhouette (SFS) lgorithm with online Region-of-Interest (ROI) estimation and binary searching, and finally construct skeleton probability visual hull with distance transform. Experiments with real video sequences show that the system can process eleven 640 × 480 video sequences at a frame rate of 15 fps, and construct human body voxels reliably in complex scenarios with cast shadows, various body configurations and multiple persons.