3-D model-based people detection & tracking

Abstract

The paper describes a method for people detection and tracking from multi-camera views. The proposed approach is based on 3D models of the person shape, where motion tracking is carried out in 3D space with re-projection onto calibrated images to perform target validation according to a prediction-verification paradigm. Multiple cameras with partial overlap can be used to cover a much wider area. The referred examples are based on the data base from PETS 2006 video sequences and a data base from EU-ISCAPS demonstration environment.