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Target coverage in camera networks for manufacturing workplaces

Author

Listed:
  • 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)

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.

Suggested Citation

  • Samer Hanoun & Asim Bhatti & Doug Creighton & Saeid Nahavandi & Phillip Crothers & Celeste Gloria Esparza, 2016. "Target coverage in camera networks for manufacturing workplaces," Journal of Intelligent Manufacturing, Springer, vol. 27(6), pages 1221-1235, December.
    • Handle: RePEc:spr:joinma:v:27:y:2016:i:6:d:10.1007_s10845-014-0946-z
    DOI: 10.1007/s10845-014-0946-z
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    References listed on IDEAS

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    1. B Suman & P Kumar, 2006. "A survey of simulated annealing as a tool for single and multiobjective optimization," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(10), pages 1143-1160, October.
    2. Eglese, R. W., 1990. "Simulated annealing: A tool for operational research," European Journal of Operational Research, Elsevier, vol. 46(3), pages 271-281, June.
    3. Jing Ai & Alhussein A. Abouzeid, 2006. "Coverage by directional sensors in randomly deployed wireless sensor networks," Journal of Combinatorial Optimization, Springer, vol. 11(1), pages 21-41, February.
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    Cited by:

    1. Thiago C. Jesus & Daniel G. Costa & Paulo Portugal & Francisco Vasques, 2022. "A Survey on Monitoring Quality Assessment for Wireless Visual Sensor Networks," Future Internet, MDPI, vol. 14(7), pages 1-26, July.

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