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Modeling and design of mobile surveillance networks using a mutational analysis approach

Networked surveillance systems provide an extended perception and distributed reasoning capability in monitored environments through the use of multiple networked sensors. The challenge for such large scale networked systems is to design an efficient modeling and analysis tool and devise stable control algorithms for accomplishing the surveillance task. Current feature (point) based visual servo and tracking techniques generally employed do not provide an optimal solution for the surveillance task. This paper presents a mutational analysis approach for shapes, and shape based control to model and design mechanisms for such active surveillance systems. The techniques of image based Hausdorff tracking and cooperative Hausdorff tracking are introduced. Finally, experimental results demonstrate the efficacy of the proposed approach for tracking targets over a large area.