SARC3D: A new 3D body model for people tracking and re-identification

Abstract

We propose a new simplified 3D body model (called SARC3D) for surveillance application, which can be created, updated and compared in real-time. People are detected and tracked in each calibrated camera, with their silhouette, appearance, position and orientation extracted and used to place, scale and orientate a 3D body model. For each vertex of the model a signature (color features, reliability and saliency) is computed from 2D appearance images and exploited for matching. This approach achieves robustness against partial occlusions, pose and viewpoint changes. The complete proposal and a full experimental evaluation are presented, using a new benchmark suite and the PETS2009 dataset. © 2011 Springer-Verlag.