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Crowd Flow Segmentation Using a Novel Region Growing Scheme

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5879))

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.

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© 2009 Springer-Verlag Berlin Heidelberg

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Wu, S., Yu, Z., Wong, HS. (2009). Crowd Flow Segmentation Using a Novel Region Growing Scheme. In: Muneesawang, P., Wu, F., Kumazawa, I., Roeksabutr, A., Liao, M., Tang, X. (eds) Advances in Multimedia Information Processing - PCM 2009. PCM 2009. Lecture Notes in Computer Science, vol 5879. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10467-1_80

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  • DOI: https://doi.org/10.1007/978-3-642-10467-1_80

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10466-4

  • Online ISBN: 978-3-642-10467-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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