Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Moving Object Detection Using SURF and Label Cluster Update in Active Camera

SURF와 Label Cluster를 이용한 이동형 카메라에서 동적물체 추출

  • 정용한 (인하대학교 정보통신공학부) ;
  • 박은수 (인하대학교 정보통신공학부) ;
  • 이형호 (인하대학교 정보통신공학부) ;
  • 왕덕창 (인하대학교 정보통신공학부) ;
  • 허욱열 (인하대학교 전기공학과) ;
  • 김학일 (인하대학교 정보통신공학부)
  • Received : 2010.10.19
  • Accepted : 2011.11.15
  • Published : 2012.01.01
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Abstract

This paper proposes a moving object detection algorithm for active camera system that can be applied to mobile robot and intelligent surveillance system. Most of moving object detection algorithms based on a stationary camera system. These algorithms used fixed surveillance system that does not consider the motion of the background or robot tracking system that track pre-learned object. Unlike the stationary camera system, the active camera system has a problem that is difficult to extract the moving object due to the error occurred by the movement of camera. In order to overcome this problem, the motion of the camera was compensated by using SURF and Pseudo Perspective model, and then the moving object is extracted efficiently using stochastic Label Cluster transport model. This method is possible to detect moving object because that minimizes effect of the background movement. Our approach proves robust and effective in terms of moving object detection in active camera system.

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References

  1. C. Wren, A. Azarbayejani, T. Darrel, and A. Pentland, "PFinder, real time tracking of the human body," IEEE PAMI, vol. 19, no. 7, Jul. 1997.
  2. C. Stauffer and Grimson, "Learning patterns of activity using real-time tracking," IEEE PAMI, vol. 22, no. 8, pp. 747-767, Aug. 2000. https://doi.org/10.1109/34.868677
  3. I. Haritaoglu, D. Harwood, and L. Davis, "W4: Real time surveillance of people and their activities," IEEE PAMI, vol. 22, no. 8, pp. 809-830, Aug. 2000. https://doi.org/10.1109/34.868683
  4. R. Cucchiara, C. Grana, M. Piccardi, and A. Prati, "Improving shadow suppression in moving object detection with HSV color information," Intelligent Transportation Systems, pp. 334-339, Aug. 2001.
  5. B. Leibe, A. Leonardis, and B. Schiele, "Robust object detection with interleaved categorization and segmentation," International Journal of Computer vision, vol. 77, pp. 259-289, May 2008. https://doi.org/10.1007/s11263-007-0095-3
  6. J. Zhou, D. Gao, and D. Zhang, "Moving vehicle detection for automatic traffic monitoring," IEEE Transaction on Vehicular Technology, vol. 56, no. 1, pp. 51-59, Jan. 2007. https://doi.org/10.1109/TVT.2006.883735
  7. O. Javed and M. Shah, "Tracking and object classification for automated surveillance," Lecture Notes in Computer Science, vol. 2353, pp. 439-443, 2006.
  8. B. Jung and G. Sukhatme, "Detecting moving object using a single camera on a mobile robot in an outdoor environment," Conference on Intelligent Autonomous Systems, pp. 980-987, Mar. 2004.
  9. D. G. Lowe, "Distinctive image features from scale invariant keypoints," International Journal of Computer Vision, vol. 60, no. 2, pp. 91-110, 2004. https://doi.org/10.1023/B:VISI.0000029664.99615.94
  10. H. Bay, T. Tuytelaars, and L. V. Gool, "SURF: Speeded up robust features," Lecture Notes in Computer Science, vol. 3951, pp. 404-417, 2006.
  11. E. Trucco and A. Verri, Introductory Techniques for 3-D Computer Vision, Prentice Hall, 1998.
  12. T. Horprasert, D. Harwood, and L. S. Davis, "A robust background subtraction and shadow detection," Proc. of Asian Conference on Computer Vision, pp. 983-988, Jan. 2000.
  13. G. R. Bradski, "Computer vision face tracking for use in a perceptual user interface," Proc. of Intel Technology Journal, vol. 2, no.2, pp. 12-21, 1998.
  14. S. J. Kim, J. W. Park, and J. M. Lee, "Implementation of tracking and capturing a moving object using a mobile robot," International Journal of Control, Automation, and Systems, vol. 3, no. 3, pp. 444-452, 2005.
  15. I. S. Kim, H. S. Choi, K. M. Yi, J. Y. Choi, and S. G. Kong, "Intelligent visual surveillance - A survey," International Journal of Control, Automation, and Systems, vol. 8, no.5, pp.926-939, 2010. https://doi.org/10.1007/s12555-010-0501-4