基于时空信息约束的密集人群分割方法

doi:10.12066/j.issn.1007-2861.1760

Journal of Shanghai University（Natural Science Edition） ›› 2017, Vol. 23 ›› Issue (5): 742-751.doi: 10.12066/j.issn.1007-2861.1760

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Segmenting groups in crowd based on spatiotemporal restraint

YI Xian^1,2, DONG Nan², WEI Jianming², ZHU Wenhao¹

1. School of Computer Engineering and Science, Shanghai University, Shanghai 200444, China;
2. Safety and Emergency Laboratory, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China

Received:2015-11-02 Online:2017-10-30 Published:2017-10-30

Abstract

Abstract:

Pedestrians in crowded scenes can be seen as a collection of groups moving coherently. To segment the crowd into groups and analyze interactions between them, a method using group spatiotemporal relationships is proposed. Spatiotemporal information of crowds by modeling the background and tracking the feature points is acquired. Then the individuals are grouped according to aspatial neighborhood restraint. The groups are further divided by motion correlation over time. These two restraints work with each other effectively, and generate groups with coherent motion. Tests on many videos of real-world pedestrian scenes show that the method can be applied to a variety of scenes with different crowd densities and perspective of videos.

Key words: coherent motion, spatiotemporal restraint, sub-group, crowd segmentation

YI Xian1,2, DONG Nan2, WEI Jianming2, ZHU Wenhao1. Segmenting groups in crowd based on spatiotemporal restraint[J]. Journal of Shanghai University（Natural Science Edition）, 2017, 23(5): 742-751.

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Segmenting groups in crowd based on spatiotemporal restraint

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