Smart Camera Networks in Virtual Reality

We present smart camera network research in the context of a unique new synthesis of advanced computer graphics and vision simulation technologies. We design and experiment with simulated camera networks within visually and behaviorally realistic virtual environments. Specifically, we demonstrate a smart camera network comprising static and active simulated video surveillance cameras that provides perceptive coverage of a large virtual public space, a train station populated by autonomously self-animating virtual pedestrians. In the context of human surveillance, we propose a camera network control strategy that enables a collection of smart cameras to provide perceptive scene coverage and perform persistent surveillance with minimal intervention. Our novel control strategy naturally addresses camera aggregation and camera handoff, it does not require camera calibration, a detailed world model, or a central controller, and it is robust against camera failures and communication.