Baltieri, DavideVezzani, RobertoCucchiara, RitaEnrico Puppo and Andrea Brogni and Leila De Floriani2014-01-272014-01-272010978-3-905673-80-7https://doi.org/10.2312/LocalChapterEvents/ItalChap/ItalianChapConf2010/065-071Wide area video surveillance always requires to extract and integrate information coming from different cameras and views. Re-identification of people captured from different cameras or different views is one of most challenging problems. In this paper, we present a novel approach for people matching with vertices-based 3D human models. People are detected and tracked in each calibrated camera, and their silhouette, appearance, position and orientation are extracted and used to place, scale and orientate a 3D body model. Colour features are computed from the 2D appearance images and mapped to the 3D model vertices, generating the 3D model for each tracked person. A distance function between 3D models is defined in order to find matches among models belonging to the same person. This approach achieves robustness against partial occlusions, pose and viewpoint changes. A first experimental evaluation is conducted using images extracted from a real camera set-up.Categories and Subject Descriptors (according to ACM CCS): I.4.8 [Image Processing and Computer Vision]: Scene Analysis-Tracking