The Human Identification Method in Video Surveillance System

영상 감시시스템에서의 휴먼인식 방법

  • 문해민 (조선대학교 정보통신공학과) ;
  • 반성범 (조선대학교 제어계측로봇공학과)
  • Published : 2010.05.31

Abstract

Recently, the use of video surveillance system including CCTV is increasing. However as the data recorded through the video surveillance system is exposed, the invasion of privacy is raised. The studies on the technology of protecting privacy in addition to these organizations are actively carried out. To distinguish the human of privacy protection, the identification technique is necessary. This paper proposes the human identification method that uses height and clothing-color information appropriate for the intelligent video surveillance system. The proposed system provides the human identification by using the smartcard and camera at the building entrance and extracts the height and clothing color information of the human. In the inside of the building installed with a camera without a smartcard reader, the identification is made by using the height and color information of the human.

최근 테러 및 범죄의 증가로 CCTV를 비롯한 보안 감시시스템의 활용이 증가하고 있다. 하지만, 영상 감시시스템을 통해 기록되는 데이터가 노출되어 발생하는 프라이버시 침해라는 문제가 제기되고 있다. 이에 기존 감시카메라 시스템에서 프라이버시를 보호하기위해 많은 연구가 진행되고 있다. 프라이버시 보호 대상자를 판단하기 위해서는 신원확인 기술이 필요하다. 본 논문에서는 대상의 키와 옷 색상 정보를 이용하여 영상 감시시스템에 적합한 신원확인 방법을 제안한다. 제안한 시스템은 건물입구에서 스마트카드와 카메라를 통해 정확한 신원확인을 하고, 대상의 키와 색상정보를 추출한다. 스마트카드 단말기가 설치되지 않고 카메라만 설치된 건물내부에서는 대상의 키와 색상정보를 이용하여 신원을 확인한다.

Keywords

References

  1. M. Langheinrich, "Privacy invasions in ubiquitous computing," In Proc. Workshop on Socially-Informed Design of Privacy Enhancing Solutions in Ubiquitous Computing, Oct., 2002.
  2. A. Westin, "Privacy and freedom," New York: Atheneum, 1967.
  3. J. Schiff, M. Meingast, Deirdre K. Mulligan, S. Sastry, and K. Goldberg, "Respectful cameras: Detecting visual markers in real-time to address privacy concerns," IEEE Intelligent Robots and Systems, pp. 971-978, Oct., 2007.
  4. I. Kitahara, K. Kogure, and N. Hagita, "Stealth vision for protecting privacy," In Proc. Int. Conf. Pattern Recognition, Vol. 4, pp. 404-407, 2004.
  5. I. Kitahara, "Interactive video surveillance by using environmental and mobile cameras," In Proc. .IEEE Automation Congress, pp. 1-6, Oct., 2008.
  6. D. H. Kim, J. Y. Lee, H. S. Yoon, and E. Y. Cha, "A Non-cooperative user authentication system in robot environments," IEEE Trans. on Comsumer Electronics, Vol. 53, No. 2, 2007.
  7. A. Bovyrin and K. Rodyushkin, "Human height prediction and roads estimation for advanced video surveillance systems," In Proc. IEEE Conf. on Advanced Video and Signal Based Surveillance, Vol. 15-16, pp. 219-223, 2005.
  8. E. Jeges, I. Kispal, and Z. Hornak, "Measuring human height using calibrated cameras," In Proc. IEEE Conf. on Human System Interactions, Vol. 25-17, pp. 755-760, 2008.
  9. Y. J. Choi, K. J. Kim, Y. Y. Nam, and W. D. Cho, "Retrieval of identical clothing images based on local color histograms," In Proc. Convergence and Hybrid Information Technology, Vol. 1, pp. 818-823, 2008.
  10. A. Criminisi, A. Zisserman, L. Van Gool, S. Bramble, and D. Compton, "A new approach to obtain height measurements from video," In Proc. of SPIE, Boston, Messachussets, USA, Vol. 3576, pp. 1-6, 1998.
  11. A. Criminisi, "Single-view metrology: algorithms and application," In Proc. 24th DAGM Symposium on Pattern Recognition, 2002.
  12. M. Gervautz and W. Purgathofer, "A simple method for color quantization: octree quantization," In Proc. New Trends in Computer Graphics, pp. 287-293, 1990.
  13. M. T. Orchard, C. A. Bouman, "Color quantization of Images," In Proc. IEEE Trans. on Signal Processing, Vol. 39. No. 12. pp. 2677-2690, 1991. https://doi.org/10.1109/78.107417
  14. M. Stricker, M. Orengo, "Similarity of color images," In Proc. Storage and Retrieval for Image and Video Databases, Vol. 2420, pp. 381-392, 1995.
  15. H. M. Moon, S. H. Chae and S. B. Pan, "The surveillance system based on RFID system for privacy protection," In Proc. Int. Conf. Computer Science and its Applications, pp. 726-731, Korea, Dec., 2009.