Optimizing Visual Surveillance Sensor Coverage Using Dynamic Programming

Abstract

Optimizing the visual sensors coverage to perform security monitoring tasks has an undeniable impact on the performance as well as the cost of video surveillance systems. The placement arrangement is an NP-hard problem, in which the main target is to seek an approximate solution. This paper addresses the placement of security cameras to maximize the total coverage of the camera network. The coverage of the visual sensor array is modeled descriptively using an enhanced pinhole camera model to obtain the layout of the field of view. The main contribution of the paper is to introduce a dynamic programming algorithm, which defines an optimal policy for solving the visual sensor coverage problem. To validate the proposed algorithm, we compared the outcomes of the dynamic programming algorithm with the existing benchmarking placement optimization techniques. The assessment reveals the effectiveness of the proposed dynamic programming solution to maximize the coverage for a set of predefined locations.