Programs
- M. Tech. in Automotive Engineering -
- Clinical Fellowship in Laboratory Genetics & Genomics - Fellowship
Publication Type : Journal Article
Publisher : IEEE Transactions on Systems, Man, and Cybernetics: Systems
Source : IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022, doi: 10.1109/TSMC.2022.3194209
Url : https://ieeexplore.ieee.org/document/9851217
Keywords : Cameras, Surveillance ,Optimization ,Buildings ,Task analysis, Robot vision systems, Heuristic algorithms
Campus : Amritapuri
School : Department of Computer Science and Engineering, School of Computing
Center : Computer Vision and Robotics
Department : Computer Science
Year : 2022
Abstract : Efficient deployment of cameras optimizes the costs and benefits in a multicamera surveillance network. Most camera placement algorithms are developed for surveillance regions with predefined camera locations, where optimal orientation for every given camera location is determined to maximize coverage. The existing approaches to optimizing the number of cameras, locations, and orientations focus on specific scenarios and are neither generic nor scalable across diverse surveillance scenarios. This article proposes a generic and scalable reward penalty score (RPS) algorithm for optimal camera placement in diverse indoor and outdoor scenarios to efficiently attain a specified coverage requirement. The camera placement decision is driven by maximizing total coverage over the surveillance region with a minimum number of cameras at optimal locations and orientations. Based on the RPS algorithm, we extend the existing Greedy grid voting (GGV) algorithm that was limited to optimizing camera orientations for predefined locations. The extended GGV (EGGV) algorithm is broader in scope and optimizes the number of cameras, their locations, and orientations. Overall, the RPS algorithm produces superior coverage results over indoor and outdoor scenarios compared to the existing camera placement algorithms on map images of diverse surveillance scenarios ranging from small to large.
Cite this Research Publication : Dr. Sumi Suresh M. S. and Dr. Vivek Menon, "A Generic and Scalable Approach to Maximize Coverage in Diverse Indoor and Outdoor Multicamera Surveillance Scenarios," in IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022, doi: 10.1109/TSMC.2022.3194209