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Accession Number ADA564527
Title Continuous Graph Partitioning for Camera Network Surveillance.
Publication Date Jul 2012
Media Count 17p
Personal Author D. Borra F. Bullo F. Pasqualetti
Abstract In this work we design surveillance trajectories for a network of autonomous cameras to detect intruders in an environment. Intruders, which appear at arbitrary times and locations, are classified as static or dynamic. While static intruders remain stationary, dynamic intruders are aware of the cameras configuration and move to avoid detection, if possible. As performance criteria we consider the worst-case detection time of static and dynamic intruders. We model the environment and the camera network by means of a robotic roadmap. We show that optimal cameras trajectories against static intruders are obtained by solving a continuous graph partitioning problem. We design centralized and distributed algorithms to solve this continuous graph partitioning problem. Our centralized solution relies on tools from convex optimization. For the distributed case we consider three distinct cameras communication models and propose a corresponding algorithm for each of the models. Regarding dynamic intruders, we identify necessary and sufficient conditions on the cameras locations to detect dynamic intruders infinite time. Additionally, we construct constant-factor optimal trajectories for the case of ring and tree roadmaps.
Keywords Algorithms
Camera network
Communication and radio systems
Convex bodies
Graph partitioning

Source Agency Non Paid ADAS
NTIS Subject Category 72B - Algebra, Analysis, Geometry, & Mathematical Logic
62 - Computers, Control & Information Theory
82B - Photographic Techniques & Equipment
Corporate Author California Univ., Santa Barbara. Center for Control Engineering and Computation.
Document Type Technical report
Title Note N/A
NTIS Issue Number 1303
Contract Number W911NF-11-1-0092

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