Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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The Walkers Tracking Algorithm using Color Informations on Multi-Video Camera

다중 비디오카메라에서 색 정보를 이용한 보행자 추적

  • 신창훈 (청주대학교 전자공학과) ;
  • 이주신 (청주대학교 전자공학과)
  • Published : 2004.08.01
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Abstract

In this paper, the interesting moving objects tracking algorithm using color information on Multi-Video camera against variance of intensity, shape and background is proposed. Moving objects are detected by using difference image method and integral projection method to background image and objects image only with hue area, after converting RGB color coordination of image which is input from multi-video camera into HSI color coordination. Hue information of the detected moving area are segmented to 24 levels from $0^{\circ}$ to $360^{\circ}$. It is used to the feature parameter of the moving objects that are three segmented hue levels with the highest distribution and difference among three segmented hue levels. To examine propriety of the proposed method, human images with variance of intensity and shape and human images with variance of intensity, shape and background are targeted for moving objects. As surveillance results of the interesting human, hue distribution level variation of the detected interesting human at each camera is under 2 level, and it is confirmed that the interesting human is tracked and surveilled by using feature parameters at cameras, automatically.

본 논문은 조도, 형태, 배경의 변화에 강인한 다중 비디오카메라에서 색 정보를 이용한 보행자 추적에 대하여 제안한다. 제안된 방법은 비디오카메라로부터 입력되는 영상의 색조만을 이용하여 배경영상과 물체가 존재하는 영상에서 차영상 기법과 가산투영 기법을 사용하여 이동물체를 검출한다. 검출된 이동물체 영역의 색조는 0도부터 360도 사이에서 15도씩 24단계로 분할된다. 검출된 이동물체 영역의 색조 분포도를 구한 후, 가장 높은 분포를 갖는 3개의 색조 레벨과 3개의 색조 레벨 사이의 차를 이동물체의 특징파라미터로 사용하였다. 제안된 방법의 유용성을 증명하기 위하여 조도와 형태의 변화가 발생한 보행자 영상과 조도, 형태, 배경의 변화가 발생한 보행자 영상을 이용하여 보행자를 감시한 결과 카메라에서 검출된 특정사람의 색조 분포 레벨과 색조 레벨 사이의 차는 2레벨 이하로 유지함을 보였고, 제안된 특징 파라미터로 특정사람이 자동 추적감시 됨을 확인하였다.

Keywords

References

  1. Tsai-Hong Hong, Tommy Chang, Chritopher Rasmusen and Michael shneier, 'Feature Detection and Tracking for Mobile Robots Using a Combination of Ladar and Color images' Proceedings of the 2002 IEEE International Conference onRobotics & Automation Washington DC May 2002, pp. 4330-4345
  2. 서동하, 임재혁, 원치선, 'HSV 칼라를 이용한 블록단위 영상 분할', 2000년 제13회 신호처리 학술대회 논문집 제13권 1호, pp. 651-654
  3. Ng Kim Piau and surendra Ranganath 'Tracking People', Pattern Recognition, 2002. Proceedings. 16th International Conference on Publication Date: 2002, vol. 2 pp. 370-373
  4. George V. Paul, Glenn J. Beach and Charles J. Cohen, 'A Realtime Object Tracking System using a Color Camera', 30th Applied Imagery Pattern Recognition Workshop (AIPR'Ol) October 10 - 12, 2001, Washington, D.C. pp. 137-142
  5. Greg T. Kogut and Mohan M. Trivedi, 'Real-time Wide Area Tracking : Hardware and Software Infrastructure', The IEEE 5th International conference on Intelligent Transportation Systems 3-6 September 2002, Singapore
  6. D. Beymer and K. Konolige, 'Real-time Tracking of Multiple People using Stereo', In IEEE Frame Rate Workshop, 1999
  7. A Bobick and J. Davis 'Real-time recognition of Activity using Temporal Templates" In IEEE Workshop on application of Computer Vision, pp. 1233-1251, 1996
  8. Ismail Haritaoglu and Myron Flickner, 'Detection and Tracking of Shopping Groups in Stores', in Proc. IEEE Conf. on Computer Vision and Pattern Recognition, Kauai, Hawaii, 2001. pp. 1-431 - 1-438
  9. Zoran Duric Fayin Li, Yan sun and Harry Wechsler, 'Using Normal flow for Detection and Tracking of Limbs in Color images'
  10. Gi-jeong Jang and In-So Kweon 'Robust Object Tracking Using an Adaptive Color Model', Proceedings of the 2001 IEEE International conference on Robotics & Automation Seoul, Korea. May 21-26, 2001, pp. 1677-1682
  11. J. Yang and A. Waibel, 'A Real-Time Face Tracker', Proceeding of WACV, pp 142-147, 1996
  12. M. J. Jones and J. M. Rehg, 'Statistical Color Models with Aplocation to Skin Detection', Proc. CVPR, pp 274-280, 1999
  13. J. Krumm, et. al., 'Multi-camera Multiperson Tracking for EasyLing', Third IEEE International Workshop on Visual Surveillance 2000, 3-10, 2000
  14. S. J. McKenna, et. al., 'Tracking Interacting People', Proceeding of Fourth IEEE Conference on Automatic Face and Gesture Recognition, 2000, 348-353 2000
  15. Rafael C. Gonzalez and Richard E. Woods, 'Digital Image Processing', Addison Wesley Longman, 1992
  16. Quan Chun, 'A Study on Real-time Tracking of Moving Object Based on Fast Matching Algorithm', Ph. D. Paper, 2003, 2
  17. Chris Stauffer and W. Eric L. Grimson, 'Learning Patterns of Activity Using Real-Time Tracking", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 22, No.8, August 2000
  18. Collins, Lipton, Kanande, Fugiyoshi, duggins, Tsin, Tolliver, Enomoto and Hasegawa, 'A System for Video surveillance and Monitoring', VSAM Fianl Report Technical Report CMURI-TR-00-12, Robotics Institute, CMU, May, 2000
  19. 김준식, 박래홍, 이병욱, '가산투영을 이용한 2단계 고속 블록 정합 알고리듬' 전자공학회논문지, 제30권, B편, 제1호, pp. 45-54, 1993