We introduce UCSB's Visual Sensor Network (VISNET) and discuss current research being conducted with the system. VISNET is a ten-node experimental camera network at UCSB used for various vision-related research. The mission of VIS-NET is to provide an easy-to-use multi-node camera network to the vision research community at UCSB. This paper briefly discusses design and setup considerations before discussing current research. Current research includes operation visualization, camera network calibration, tracked object modeling, and multiple object / multiple camera tracking.

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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, 7π 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.

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