Towards a visual-hull based multi-agent surveillance system

We present a multi-view three dimensional intelligent surveillance system. We use a multi-agent framework to identify the behaviors of individuals in the scene. Detection and interpretation are performed completely in 3D space. A moving train coach is monitored by eight fish-eye cameras. Segmentation masks extracted from the undistorted images are fed to a distributed 3D reconstruction algorithm producing an octree-based description of the volume at each frame. Voxel-based algorithms extract connected-regions and their descriptions from consecutive models. The set of regions is mapped to a set of agents. We achieve dynamically consistent high-level interpretations by combining probabilistic models of human behaviors and intelligent reasoning.