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Detection of Salient Crowd Motion Based on Repulsive Force Network and Direction Entropy

1
School of Communication Engineering, Hangzhou Dianzi University, Hangzhou 310018, China
2
School of Electrical Engineering, Shandong Huayu University of Technology, Dezhou 253034, China
3
School of Creative Technologies, University of Portsmouth, Portsmouth PO1 2DJ, UK
*
Authors to whom correspondence should be addressed.
Entropy 2019, 21(6), 608; https://doi.org/10.3390/e21060608
Received: 8 May 2019 / Revised: 17 June 2019 / Accepted: 18 June 2019 / Published: 20 June 2019
(This article belongs to the Special Issue Entropy in Image Analysis II)
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PDF [7692 KB, uploaded 20 June 2019]
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Abstract

This paper proposes a method for salient crowd motion detection based on direction entropy and a repulsive force network. This work focuses on how to effectively detect salient regions in crowd movement through calculating the crowd vector field and constructing the weighted network using the repulsive force. The interaction force between two particles calculated by the repulsive force formula is used to determine the relationship between these two particles. The network node strength is used as a feature parameter to construct a two-dimensional feature matrix. Furthermore, the entropy of the velocity vector direction is calculated to describe the instability of the crowd movement. Finally, the feature matrix of the repulsive force network and direction entropy are integrated together to detect the salient crowd motion. Experimental results and comparison show that the proposed method can efficiently detect the salient crowd motion. View Full-Text
Keywords: crowd behavior analysis; salient crowd motion detection; repulsive force; direction entropy; node strength crowd behavior analysis; salient crowd motion detection; repulsive force; direction entropy; node strength
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Zhang, X.; Lin, D.; Zheng, J.; Tang, X.; Fang, Y.; Yu, H. Detection of Salient Crowd Motion Based on Repulsive Force Network and Direction Entropy. Entropy 2019, 21, 608.

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