%X The research work on camera placement has focused on maximizing the coverage or minimizing the installation cost of video surveillance systems. Typical placement schemes mount surveillance cameras with no emphasis on the coverage demand divergences, which impacts the system's cost and efficiency. This paper addresses the camera placement problem based on an inverse modeling taxonomy. Thus, rather than performing the optimization on uniformly distributed grids, this paper introduces an underlying mechanism to elaborate the security sensitive zones prior to the coverage optimization. The outcome of the prioritization process is termed as Risk Maps. Obtained empirical results show the reliability of the placement using inverse modeling. Finally, the validation of the proposed placement scheme is carried out in a constraint environment. © 1963-2012 IEEE.
%K Cameras; Maps; Security systems, Camera placement; Coverage optimizations; Installation costs; Inverse modeling; Placement scheme; Prioritization process; Surveillance cameras; Video surveillance systems, Inverse problems
%D 2020
%N 6
%R 10.1109/TIM.2019.2927650
%O cited By 10
%J IEEE Transactions on Instrumentation and Measurement
%L scholars13109
%T Visual Sensor Placement Based on Risk Maps
%V 69
%I Institute of Electrical and Electronics Engineers Inc.
%A A.A. Altahir
%A V.S. Asirvadam
%A N.H.B. Hamid
%A P. Sebastian
%A M.A. Hassan
%A N.B. Saad
%A R. Ibrahim
%A S.C. Dass
%P 3109-3117