A simpler linear time 2/3 - ε approximation for maximum weight matching
Information Processing Letters
A Prototype of Autonomous Intelligent Surveillance Cameras
AVSS '06 Proceedings of the IEEE International Conference on Video and Signal Based Surveillance
The effects of synchronization on topology-transparent scheduling
Wireless Networks
Distributed approximate matching
Proceedings of the twenty-sixth annual ACM symposium on Principles of distributed computing
Graph Theory
Target tracking with distributed sensors: The focus of attention problem
Computer Vision and Image Understanding - Special issue: Attention and performance in computer vision
Optimal placement and selection of camera network nodes for target localization
DCOSS'06 Proceedings of the Second IEEE international conference on Distributed Computing in Sensor Systems
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
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The effectiveness of the surveillance (monitoring a set of mobile targets with a set of cameras) depends on the resolution of the monitored images and the duration for which the targets are monitored. PTZ cameras are a natural choice to maintain a desired level of resolution for mobile targets. Maintaining resolution by controlling the camera parameters above a desired threshold value, however, implies that the field of regard of a camera cannot be arbitrarily broadened to include multiple targets. Camera for each target needs to be judiciously chosen to ensure monitoring for prolonged time interval. In this paper we propose a metric viz. average effective monitoring time (AEMT), towards capturing the effectiveness of video based surveillance. To achieve enhanced AEMT, we formulate an optimization problem in terms of associating cameras with the targets based on an appropriate weight function and design an efficient distributed algorithm. Simulation results show that our approach contributes significantly towards improving AEMT.