Detecting interaction/complexity within crowd movements using braid entropy

Murat AKPULAT; Murat EKİNCİ

doi:10.1631/FITEE.1800313

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Detecting interaction/complexity within crowd movements using braid entropy

Regular Papers | Updated：2022-05-19

- Detecting interaction/complexity within crowd movements using braid entropy
- 利用编织熵探测人群运动的相互作用/复杂程度
- Frontiers of Information Technology & Electronic Engineering Vol. 20, Issue 6, Pages: 849-861(2019)
- Affiliations：
  
  Kelkit Aydın Doğan Vocational School, Gmşhane University, Gmşhane 29100, Turkey
  Department of Computer Engineering, Karadeniz Technical University, Trabzon 61080, Turkey
- Author bio：
  
  Murat AKPULAT, E-mail: muratakpulat@gumushane.edu.tr
  [ "Murat EKİNCİ, E-mail: mekinci@ktu.edu.tr" ]
- Funds：
- DOI：10.1631/FITEE.1800313
  CLC： TP391.4
- Received：20 May 2018，
  
  Revised：2019-;6-11，
  
  Published：2019-06
- Accepted：
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Murat AKPULAT, Murat EKİNCİ. Detecting interaction/complexity within crowd movements using braid entropy[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(6): 849-861.
DOI：

Murat AKPULAT, Murat EKİNCİ. Detecting interaction/complexity within crowd movements using braid entropy[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(6): 849-861. DOI： 10.1631/FITEE.1800313.

摘要

在群体分析领域中，图像运动与非运动区域分割对理解大众行为至关重要。在许多研究中，相似的运动可根据位置、彼此邻接、方向及平均速度分割。然而，这样的分割不可能反过来表明各自区域内相同行为类型。本文目的是通过局部测量分割片段内的相互作用/复杂程度，更好地理解大众行为。为此，图像中运动的流动主要由一系列轨迹表达，且图像被分割为诸多六边形单元。根据各单元不同投影角度，可计算出有限时间编织熵（FTBE）值。该值取决于运动轨迹螺旋形结构的复杂性，并展示了行人间相互作用程度。本文将分割片段内所确定的不同复杂度的行为视作整体上的相似运动，测试了49个来自UCF和CUHK数据库的不同视频系列。

Abstract

The segmentation of moving and non-moving regions in an image within the field of crowd analysis is a crucial process in terms of understanding crowd behavior. In many studies

similar movements were segmented according to the location

adjacency to each other

direction

and average speed. However

these segments may not in turn indicate the same types of behavior in each region. The purpose of this study is to better understand crowd behavior by locally measuring the degree of interaction/complexity within the segment. For this purpose

the flow of motion in the image is primarily represented as a series of trajectories. The image is divided into hexagonal cells and the finite time braid entropy (FTBE) values are calculated according to the different projection angles of each cell. These values depend on the complexity of the spiral structure that the trajectories generated throughout the movement and show the degree of interaction among pedestrians. In this study

behaviors of different complexities determined in segments are pictured as similar movements on the whole. This study has been tested on 49 different video sequences from the UCF and CUHK databases.

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Keywords

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