Browse > Article

Robust Detection of Abandoned Objects Using Visual Context  

Lee, Jung-Hyun (Dept. of Image Engineering, Graduate School of Advanced Image Science, Multimedia, and Film, Chung-Ang University)
Im, Jae-Hyun (Dept. of Image Engineering, Graduate School of Advanced Image Science, Multimedia, and Film, Chung-Ang University)
Paik, Joon-Ki (Dept. of Image Engineering, Graduate School of Advanced Image Science, Multimedia, and Film, Chung-Ang University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.49, no.3, 2012 , pp. 60-66 More about this Journal
Abstract
In this paper, we propose abandoned object detection algorithm. When abandoned object was occluded other object, the existing methods cannot detect abandoned object because those methods are not able to estimate the location of abandoned object. In order to overcome this problem, the proposed algorithm extracts the corners around abandoned object. The detected corners are linked to center of abandoned object called by supporters. We can then estimate the location of abandoned object by using supporters. Therefore, the proposed algorithm can detect and estimate the location of abandoned object, when abandoned object is occluded by other object. For this reason, the proposed algorithm can be applied to intelligent surveillance system to prevent bomb terror, which disguises as luggage or box.
Keywords
Abandoned object detection; Supporter; Intelligent video surveillance;
Citations & Related Records
연도 인용수 순위
  • Reference
1 A. Singh, S. Sawan, M. Hanmandlu, V. Madasu, and B. Lovell, "An abandoned object detection system based on dual background segmentation," IEEE Conf. Advanced Video, Signal Based Surveillance, pp. 352-357, September 2009.
2 X. Li and D. Zhang, "Abandoned objects detection using double illumination invariant foreground masks," IEEE Conf. Int. Conf. Pattern Recognition, pp. 436-439, August 2010.
3 P. Spagnolo, A. Caroppo, M. Leo, T. Martiriggiano, and T. D'Orazio, "An abandoned/removed objects detection algorithm and its evaluation on PETS datasets," Proc. Int. Conf. Video, Signal Based Surveillance, pp.17-21, November 2006.
4 T. Kim, J. Im, and J. Paik, "Video object segmentation and its salient motion detection using adaptive background generation," IET Electronics Letters, vol. 45, pp. 542-543, May 2009.   DOI   ScienceOn
5 C. Harris and M. Stephens, "A combined corner and edge detector," Proc. Alvey Vision Conference, pp. 147-151, 1998.
6 IEEE International Workshop on Advanced Video, Signal based Surveillance, London, September 2007.