The Journal of Korean Institute of Communications and Information Sciences (한국통신학회논문지)

The Korean Institute of Commucations and Information Sciences (한국통신학회)
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A Study on the Object Extraction and Tracking System for Intelligent Surveillance

지능형 감시를 위한 객체추출 및 추적시스템 설계 및 구현

  • Received : 2013.05.27
  • Accepted : 2013.07.09
  • Published : 2013.07.31
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Abstract

The agents for security surveillance are not enough for monitoring CCTV system, so the intelligent automatic surveillance system is needed. In this paper, object detection, tracking and abnormal event detection system is implemented for intelligent CCTV system. Each modules are tested on the real CCTV environment and promoted for commercialization. Abnormal event detection module and loitering detection and sudden running detection function and it's detection time is under 1 second which is satisfied level.

최근 보안 관제를 위한 인원부족 및 감시 능력의 한계로 자동화된 지능형 관제 시스템에 대한 요구가 증가하고 있다. 이 논문에서는 지능형 감시시스템의 구축을 위하여 자동화된 객체추출 및 추적 시스템, 그리고 이상행위를 인지하는 이상행위 검출 시스템을 설계하고 구현하였다. 각 모듈은 기존의 연구 결과를 바탕으로 실제 환경에서 적용되고 상용화가 가능하도록 알고리즘의 성능을 높였으며, 구현 후 다양한 테스트를 통해 그 성과를 검증하였다. 특히, 배회 또는 도주와 같은 이상행위의 경우 1초 이내에 검출할 수 있었다.

Keywords

References

  1. Ministry of Police, The police white paper, pp. 353, Sep., 2010.
  2. W. J. Kim, "CCTV market flow and estimation," EIC, Jul. 2011.
  3. C. Y. Jung and J. W. Han, "Intelligent image analysis event detection technology trend," Electron. Telecommun. Trends, vol. 27, no. 4, pp. 114-122, Aug. 2012.
  4. M. Cetin, W. C. Karl, and A. S. Willsky, "Edge-preserving image reconstruction for coherent imaging applications," in Proc. 2002 Int. Conf. Image Process., vol. 2, pp. 481-484, Rochester, U.S.A., Sep. 2002.
  5. Z. Lin, "Using dynamic wavelets to reduce the ringing artifacts in NMR images," Pattern Recognition and Artificial Intell., vol. 12, no. 3, pp. 320-324, May 1999.
  6. H. Kim, R. Sakamoto, I. Kitahara, T. Toriyama, and K. Kogure, "Robust foreground segmentation from color video sequences using background subtraction with multiple thresholds," IEIC Tech. Report, vol. 106, no. 376, pp. 135-140, Nov. 2006.
  7. A. Bissacco, P. Saisan, and S. Soatto, "Gait recognition using dynamic affine invariants," in Proc. Int. Symp. Math. Theory Networks Syst. (MTNS'04), Leuven, Belgium, July 2004.
  8. S. Lee, 400 CCTV installed in An-san U-city in 2nd stage, Retrieved Nov, 11, 2012, from http://cctvnews.co.kr/.
  9. ITX, Retrieved June, 30, 2013, from http://www.itxsecurity.co.kr/.
  10. IBM, Retrieved June, 30, 2013, from http://www-935.ibm.com/services/us/iss/html/se curity-solutions-for-a-smarter-planet.html
  11. AXIS Communications, Retrieved June, 30, 2013, from http://www.axis.com/
  12. E. Auvinet, E. Grossmann, C. Rougier, M. Dahmane, and J. Meunier, "Left-luggage detection using homographies and simple heuristics," in Proc. IEEE Int. Workshop Performance Evaluation Tracking Surveillance (PETS), pp. 51-58, New York, U.S.A., June 2006.
  13. Newsis, CCTV 300million era, Retrieved Oct., 2011, from http://www.newsis.com.
  14. YTN, Lack of CCTV Agents, Retrieved Sep., 2011, from http://www.ytn.co.kr.
  15. S. Fleck and W. Straber, "Privacy sensitive surveillance for assisted living a smart camera approach," Handbook of Ambient Intelligence and Smart Environments, Springer, pp 985-1014, 2010.
  16. British Home Office, Imagery Library for Intelligent Detection Systems, Retrieved June, 30th, 2012, from https://www.gov.uk/imagery-library-for-intellige nt-detection-systems#event-detection-scenario.
  17. Center for the protection of national infrastructure (CPNI), The i-LIDS User Guide, Britigh Home Office, 2011.
  18. J. H. Jeon, T. K. An, H. M. Kim, K. Y. Park, and G. M. Park, "A field test and analysis for intelligent urban transit surveillance system," in Proc. KICS Summer Conf. 2011, pp. 624-625, Jeju Island, Korea, June 2011.