Zi Ye
ABSTRACT
Crowd density estimation, is much valuable in intelligent crowd monitoring. The traditional approach based on static texture analysis of single frame, is not adept to complex background, and the rule based statistic approaches are short of robustness for background noise. In this paper, a crowd density estimation approach fusing statistic features and texture analysis was proposed. After extracting foreground objects with frame difference, we learn SVM classifiers with GLCM and statistical features. The experiment results show the superiority of the proposed method and it can be applied in a complex environment.
- Davies A C, Yin J H, Velastin S A, et al. Crowd Monitoring Using Image Processing{J}. IEEE Elect ronics and Commu2 nication Engineering Journal, 1995, 7 (1): 37--47Google Scholar
- Valle J D, Oliveira L E S. People counting in low density video sequences{C}//LNCS 4872: PSIVT 2007, 2007: 737--748. Google ScholarDigital Library
- Li Chen, Ji Tao. People counting using iterative mean- shift fitting with symmetry measure{C}//International Conference on Information and Communication Security, 2007: 890--895.Google Scholar
- Bozzoli M. A statistical method for people counting in crowded environments{C}//14th International Conference on Image Analysis and Processing (ICIAP 2007), 2007: 1110--1115. Google ScholarDigital Library
- Ma Ruihua, Li Liyuan. On pixel count based crowd density estimation for visual surveillance{C}//Proceedings of the 2004 IEEE Conference on Cybernetics and Intelligent Systems, 2004:170--173.Google Scholar
- Marana A N, Cavenaghi M A. Real-time crowd density estimation using images{C}//International Symposium on Visual Computing (ISVC 2005), 2005: 355--362. Google ScholarDigital Library
- A.B. Chan, Privacy Preserving Crowd Monitoring: Counting People with-out People Models or Tracking. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR2008), 2008.Google ScholarCross Ref
Index Terms
- Multiple features fusion for crowd density estimation
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