Robust Real-Time Face Detection
International Journal of Computer Vision
Task allocation via self-organizing swarm coalitions in distributed mobile sensor network
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Assigning cameras to subjects in video surveillance systems
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Scalable target coverage in smart camera networks
Proceedings of the Fourth ACM/IEEE International Conference on Distributed Smart Cameras
Video surveillance with PTZ cameras: the problem of maximizing effective monitoring time
ICDCN'10 Proceedings of the 11th international conference on Distributed computing and networking
Autonomic mobile sensor network with self-coordinated task allocation and execution
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Multitarget Visual Tracking Based Effective Surveillance With Cooperation of Multiple Active Cameras
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Coverage management for mobile targets in visual sensor networks
Proceedings of the 15th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems
Temporal encoded F-formation system for social interaction detection
Proceedings of the 21st ACM international conference on Multimedia
Online control of active camera networks for computer vision tasks
ACM Transactions on Sensor Networks (TOSN)
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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This paper presents a novel decision-theoretic approach to control and coordinate multiple active cameras for observing a number of moving targets in a surveillance system. This approach offers the advantages of being able to (a) account for the stochasticity of targets' motion via probabilistic modeling, and (b) address the trade-off between maximizing the expected number of observed targets and the resolution of the observed targets through stochastic optimization. One of the key issues faced by existing approaches in multi-camera surveillance is that of scalability with increasing number of targets. We show how its scalability can be improved by exploiting the problem structure: as proven analytically, our decision-theoretic approach incurs time that is linear in the number of targets to be observed during surveillance. As demonstrated empirically through simulations, our proposed approach can achieve high-quality surveillance of up to 50 targets in real time and its surveillance performance degrades gracefully with increasing number of targets. We also demonstrate our proposed approach with real AXIS 214 PTZ cameras in maximizing the number of Lego robots observed at high resolution over a surveyed rectangular area. The results are promising and clearly show the feasibility of our decision-theoretic approach in controlling and coordinating the active cameras in real surveillance system.