A Lightweight Multiview Tracked Person Descriptor for Camera Sensor Networks

Michael J. Quinn Thomas Kuo B.S. Manjunath
University of California - Santa Barbara
Department of Electrical and Computer Engineering
Santa Barbara, CA 93106
{mquinn,thekuo,manj} [at] ece.ucsb.edu


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*PI/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.
[PDF] [BibTex]
Michael J. Quinn and Thomas Kuo and B.S. Manjunath,
Proc. IEEE International Conference on Image Processing, pp. 1976-1979, San Diego, CA, Oct. 2008.
Node ID: 504 , DB ID: 311 , Lab: VRL , Target: Conference