Optimizing Visual Sensors Placement with Risk Maps Using Dynamic Programming

Typically, optimizing the poses and placement of surveillance cameras is usually formulated as a discrete combinatorial optimization problem. The traditional aspects of solving the camera placement problem attempt to maximize the area monitored by the camera array and/or reduce the cost of installin...

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Main Authors: Altahir, A.A., Asirvadam, V.S., Sebastian, P., Hamid, N.H.B., Ahmed, E.F.
Format: Article
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.28920 /
Published: Institute of Electrical and Electronics Engineers Inc. 2022
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85120043858&doi=10.1109%2fJSEN.2021.3127989&partnerID=40&md5=8846d1ebd5eb88e4ccef76d851f9877b
http://eprints.utp.edu.my/28920/
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spelling utp-eprints.289202022-03-16T08:43:15Z Optimizing Visual Sensors Placement with Risk Maps Using Dynamic Programming Altahir, A.A. Asirvadam, V.S. Sebastian, P. Hamid, N.H.B. Ahmed, E.F. Typically, optimizing the poses and placement of surveillance cameras is usually formulated as a discrete combinatorial optimization problem. The traditional aspects of solving the camera placement problem attempt to maximize the area monitored by the camera array and/or reduce the cost of installing a set of surveillance cameras. Several approximate optimization techniques have been proposed to locate near-optimal solution to the placement problem. Thus, related surveillance planning methods optimize the placement of visual sensors based on equally significance grids by not limiting to demand of coverage. This article explores the efficiency of the visual sensor placement based on a combination of two methods namely, a deterministic risk estimation for the risk assessment and a dynamic programming for optimizing the placement of surveillance cameras. That is, the enhanced efficiency of coverage is obtained by developing a prior grid assessment practice to stress on the security sensitive zones. Then, the dynamic programming algorithm operates on security quantified maps rather than uniform grids. The attained result is compared to the respective heuristic search algorithm outcomes. The overall assessment shows the reliability of the proposed methods' combinations. © 2001-2012 IEEE. Institute of Electrical and Electronics Engineers Inc. 2022 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85120043858&doi=10.1109%2fJSEN.2021.3127989&partnerID=40&md5=8846d1ebd5eb88e4ccef76d851f9877b Altahir, A.A. and Asirvadam, V.S. and Sebastian, P. and Hamid, N.H.B. and Ahmed, E.F. (2022) Optimizing Visual Sensors Placement with Risk Maps Using Dynamic Programming. IEEE Sensors Journal, 22 (1). pp. 393-404. http://eprints.utp.edu.my/28920/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description Typically, optimizing the poses and placement of surveillance cameras is usually formulated as a discrete combinatorial optimization problem. The traditional aspects of solving the camera placement problem attempt to maximize the area monitored by the camera array and/or reduce the cost of installing a set of surveillance cameras. Several approximate optimization techniques have been proposed to locate near-optimal solution to the placement problem. Thus, related surveillance planning methods optimize the placement of visual sensors based on equally significance grids by not limiting to demand of coverage. This article explores the efficiency of the visual sensor placement based on a combination of two methods namely, a deterministic risk estimation for the risk assessment and a dynamic programming for optimizing the placement of surveillance cameras. That is, the enhanced efficiency of coverage is obtained by developing a prior grid assessment practice to stress on the security sensitive zones. Then, the dynamic programming algorithm operates on security quantified maps rather than uniform grids. The attained result is compared to the respective heuristic search algorithm outcomes. The overall assessment shows the reliability of the proposed methods' combinations. © 2001-2012 IEEE.
format Article
author Altahir, A.A.
Asirvadam, V.S.
Sebastian, P.
Hamid, N.H.B.
Ahmed, E.F.
spellingShingle Altahir, A.A.
Asirvadam, V.S.
Sebastian, P.
Hamid, N.H.B.
Ahmed, E.F.
Optimizing Visual Sensors Placement with Risk Maps Using Dynamic Programming
author_sort Altahir, A.A.
title Optimizing Visual Sensors Placement with Risk Maps Using Dynamic Programming
title_short Optimizing Visual Sensors Placement with Risk Maps Using Dynamic Programming
title_full Optimizing Visual Sensors Placement with Risk Maps Using Dynamic Programming
title_fullStr Optimizing Visual Sensors Placement with Risk Maps Using Dynamic Programming
title_full_unstemmed Optimizing Visual Sensors Placement with Risk Maps Using Dynamic Programming
title_sort optimizing visual sensors placement with risk maps using dynamic programming
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2022
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85120043858&doi=10.1109%2fJSEN.2021.3127989&partnerID=40&md5=8846d1ebd5eb88e4ccef76d851f9877b
http://eprints.utp.edu.my/28920/
_version_ 1741197170323750912
score 11.62408

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