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High-density crowd behaviors segmentation based on dynamical systems

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Abstract

High-density crowd segmentation is one of the most important components in a wide range of applications in group analysis, but the complexity and variability of the high-density crowd environment make high-density crowd behaviors segmentation facing great challenges. In this paper, we introduce a holistic approach to perform segmentation using the stability analysis based on dynamical systems. This method assumes that a grid of particles is placed over the image and moved with the underlying flow field, then computes the streaklines through those moving particles. After through a novel similarity calculation method to compute the similarity of streaklines, we capture different crowd behaviors to realize crowd segmentation. Experimental results prove the effectiveness of our algorithm.

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Authors and Affiliations

  1. Department of Information Engineering, China Jiliang University, Hangzhou, China

    Dongping Zhang, Jiao Xu, Min Sun & Zhiyu Xiang

Authors
  1. Dongping Zhang
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  2. Jiao Xu
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  3. Min Sun
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  4. Zhiyu Xiang
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Corresponding author

Correspondence to Dongping Zhang.

Additional information

Communicated by T. Plagemann.

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Zhang, D., Xu, J., Sun, M. et al. High-density crowd behaviors segmentation based on dynamical systems. Multimedia Systems 23, 599–606 (2017). https://doi.org/10.1007/s00530-016-0520-y

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  • DOI: https://doi.org/10.1007/s00530-016-0520-y

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