Crowd Flow Segmentation Using a Novel Region Growing Scheme

Authors:
Si Wu;Zhiwen Yu;Hau-San Wong
Affiliations:
Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong;Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong and School of Computer Science and Engineering, South China University of Technology, Guangzhou, China;Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong
Venue:
PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Year:
2009

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Abstract

Segmenting and analyzing crowd flow from surveillance videos is effective for monitoring abnormal motion or reducing incidents in a crowd scene. In this paper, we use translation flow to approximate local crowd motion and propose a novel region growing scheme to segment crowd flow based on optical flow field. We improve the model of translation domain segmentation and adapt it to a general vector field. To implement flow segmentation, the domain's contour determined by a set of boundary points is adaptively updated by shape optimization in the improved model. The experiments based on a set of crowd videos show that the proposed approach has the capability to segment crowd flow for further analysis.