We present a simple multiple view 3D model for object tracking and identification in camera networks. Our model is composed of 8 distinct views in the interval 0, 7 4 . Each of the 8 parts describes the person's appearance from that particular viewpoint. The model contains both color and structure information about each view which are assembled into a single entity and is meant as a simple, lightweight object representation for use in camera sensor networks. It is versatile in that it can be gradually assembled on-line while a person is tracked. The model's ease of use and effectiveness for identification in surveillance video is demonstrated.
Michael J. Quinn, Thomas Kuo, B. S. Manjunath