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Maximizing Camera Coverage in Multi-camera Surveillance Networks

Publication Type : Journal Article

Publisher : IEEE Sensors Journal, IEEE

Source : IEEE Sensors Journal, vol. 20, no. 17, pp. 10170-10178, 2020, doi: 10.1109/JSEN.2020.2992076.

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Keywords : Camera placement, greedy search methods, Optimization methods, Video surveillance, visual sensors

Campus : Amritapuri

School : Department of Computer Science and Engineering, School of Computing, School of Engineering

Center : Computer Vision and Robotics

Department : Computer Science

Year : 2020

Abstract : Efficient placement of cameras to perform surveillance tasks has a significant impact on the overall performance as well as cost of video surveillance systems. Identifying an optimal configuration for cameras in a surveillance system to maximize coverage is a combinatorial optimization problem. This paper proposes two algorithms for identifying optimal camera configuration for a multi-camera network with predefined camera locations. We propose an Alternate Global Greedy (AGG) algorithm, a novel variant of the Global Greedy algorithm by making significant modifications to the traditional execution strategy to produce better coverage results. Additionally, we propose an innovative Greedy Grid Voting (GGV) algorithm, which gives preference to cover unique as well as critical regions and effectively addresses a broad range of coverage scenarios mandated by the application. The proposed algorithms are validated on map images across diverse scenarios with predefined camera locations. Experimental results show that our algorithms maximize the coverage results with minimal overlap, compared to the existing greedy techniques.

Cite this Research Publication : Dr. Sumi Suresh M. S., Dr. Athinarayanan S., and Dr. Vivek Menon, “Maximizing Camera Coverage in Multi-camera Surveillance Networks”, IEEE Sensors Journal, vol. 20, no. 17, pp. 10170-10178, 2020, doi: 10.1109/JSEN.2020.2992076.

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