Multi-object shape estimation and tracking from silhouette cues

This paper deals with the 3D shape estimation from silhouette cues of multiple moving objects in general indoor or outdoor 3D scenes with potential static obstacles, using multiple calibrated video streams. Most shape-fromsilhouette techniques use a two-classification of space occupancy and silhouettes, based on image regions that match or disagree with a static background appearance model. Binary silhouette information becomes insufficient to unambiguously carve 3D space regions as the number and density of dynamic objects increases. In such difficult scenes, multi-view stereo methods suffer from visibility problems, and rely on color calibration procedures tedious to achieve outdoors. We propose a new algorithm to automatically detect and reconstruct scenes with a variable number of dynamic objects. Our formulation distinguishes between m different shapes in the scene by using automatically learnt view-specific appearance models, eliminating the color calibration requirement. Bayesi...

• Type: Conference
• Year: 2008
• Where: CVPR
• Authors: Li Guan, Jean-Sébastien Franco, Marc Pollefeys
• Keywords: Binary Silhouette Information, Computer Vision, CVPR 2008, Dynamic Objects Increases, Multiple Moving Objects, Outdoor 3d Scenes, Silhouette Scene Analysis