Target coverage in camera networks for manufacturing workplaces

Samer Hanoun (), Asim Bhatti (), Doug Creighton (), Saeid Nahavandi (), Phillip Crothers () and Celeste Gloria Esparza ()
Additional contact information
Samer Hanoun: Deakin University
Asim Bhatti: Deakin University
Doug Creighton: Deakin University
Saeid Nahavandi: Deakin University
Phillip Crothers: Boeing Research & Technology
Celeste Gloria Esparza: GM Holden

Journal of Intelligent Manufacturing, 2016, vol. 27, issue 6, No 6, 1235 pages

Abstract: Abstract In this paper, we investigate the camera network placement problem for target coverage in manufacturing workplaces. The problem is formulated to find the minimum number of cameras of different types and their best configurations to maximise the coverage of the monitored workplace such that the given set of target points of interest are each k-covered with a predefined minimum spatial resolution. Since the problem is NP-complete, and even NP-hard to approximate, a novel method based on Simulated Annealing is presented to solve the optimisation problem. A new neighbourhood generation function is proposed to handle the discrete nature of the problem. The visual coverage is modelled using realistic and coherent assumptions of camera intrinsic and extrinsic parameters making it suitable for many real world camera based applications. Task-specific quality of coverage measure is proposed to assist selecting the best among the set of camera network placements with equal coverage. A 3D CAD of the monitored space is used to examine physical occlusions of target points. The results show the accuracy, efficiency and scalability of the presented solution method; which can be applied effectively in the design of practical camera networks.

Keywords: Camera networks; Camera network placement; Simulated annealing; Target coverage; Quality of coverage (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10845-014-0946-z

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