skip to main content
10.1145/2069131.2069164acmconferencesArticle/Chapter ViewAbstractPublication PagesmobicomConference Proceedingsconference-collections
poster

Target-oriented coverage maximization in visual sensor networks

Published:31 October 2011Publication History

ABSTRACT

Visual sensor networks (VSNs) are networks made up of a possibly large number of cameras that together monitor an area or targets of interest. In VSNs, camera coverage control is necessary to allow automatic tracking of targets without human intervention, allowing these systems to scale. In this paper, we consider the problem of automatic control of cameras to maximize the number of targets covered. This is an NP-hard problem, and efficient centralized and semi-centralized heuristics exist that provide near-optimal performance. However, such schemes are hard to scale with the size of the network, and thus demand for efficient distributed solutions. The existing distributed approach results in significantly less coverage, compared to the optimal. In this paper, we extend the existing approach by considering inter-dependencies among cameras and target distributions, and show that the proposed techniques significantly improve the performance of the distributed solution.

References

  1. J. Ai and A. Abouzeid. Coverage by directional sensors in randomly deployed wireless sensor networks. Journal of Combinatorial Optimization, 2006.Google ScholarGoogle ScholarCross RefCross Ref
  2. I. Akyildiz, T. Melodia, and K. Chowdhury. A survey on wireless multimedia sensor networks. Computer Networks, 51(4):921--960, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. C. Bettstetter, M. Gyarmati, and U. Schilcher. An inhomogeneous spatial node distribution and its stochastic properties. In Proceedings of the 10th ACM Symposium on Modeling, analysis, and simulation of wireless and mobile systems, page 404. ACM, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. M. Garcia and A. Solanas. 3D simultaneous localization and modeling from stereo vision. In Robotics and Automation, 2004. Proceedings. ICRA'04. 2004 IEEE International Conference on, volume 1, pages 847--853. IEEE, 2004.Google ScholarGoogle ScholarCross RefCross Ref
  5. N. Krahnstoever, T. Yu, S. Lim, K. Patwardhan, and P. Tu. Collaborative Real-Time Control of Active Cameras in Large Scale Surveillance Systems. In Workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications, 2008.Google ScholarGoogle Scholar
  6. H. Ma, X. Zhang, and A. Ming. A coverage-enhancing method for 3d directional sensor networks. In Proc. INFOCOM Mini-conference, pages 2791--2795, 2009.Google ScholarGoogle ScholarCross RefCross Ref
  7. V. Munishwar and N. Abu-Ghazaleh. Scalable Target Coverage in Smart Camera Networks. In ACM/IEEE International Conference on Distributed Smart Cameras, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. F. Z. Qureshi and D. Terzopoulos. Surveillance camera scheduling: a virtual vision approach. In VSSN '05: Proceedings of the third ACM international workshop on Video surveillance & sensor networks, pages 131--140, New York, NY, USA, 2005. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Q. Simulator. Scalable Network Technologies. Inc. {Online}. Available: www.qualnet.com.Google ScholarGoogle Scholar
  10. S. Soro and W. Heinzelman. A survey of visual sensor networks. Advances in Multimedia, (640386):1--21, 2009.Google ScholarGoogle Scholar
  11. D. Tao, H. Ma, and L. Liu. Coverage-enhancing algorithm for directional sensor networks. Lecture Notes in Computer Science, 4325/2006:256--267, 2006.Google ScholarGoogle ScholarCross RefCross Ref
  12. J. Urrutia. Art gallery and illumination problems. Handbook of Computational Geometry, pages 973--1027, 2000.Google ScholarGoogle ScholarCross RefCross Ref
  13. C. Wang, C. Thorpe, and A. Suppe. Ladar-based detection and tracking of moving objects from a ground vehicle at high speeds. In Proceedings of Intelligent Vehicles Symposium. IEEE, 2003.Google ScholarGoogle Scholar

Index Terms

  1. Target-oriented coverage maximization in visual sensor networks

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Conferences
        MobiWac '11: Proceedings of the 9th ACM international symposium on Mobility management and wireless access
        October 2011
        218 pages
        ISBN:9781450309011
        DOI:10.1145/2069131
        • General Chair:
        • Jose Rolim,
        • Program Chairs:
        • Jun Luo,
        • Sotiris Nikoletseas

        Copyright © 2011 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 31 October 2011

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • poster

        Acceptance Rates

        Overall Acceptance Rate83of272submissions,31%

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader