Full Text:   <1852>

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CLC number: TP391.4

On-line Access: 2019-07-08

Received: 2018-05-20

Revision Accepted: 2018-09-07

Crosschecked: 2019-06-11

Cited: 0

Clicked: 5317

Citations:  Bibtex RefMan EndNote GB/T7714


Murat Akpulat


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Frontiers of Information Technology & Electronic Engineering  2019 Vol.20 No.6 P.849-861


Detecting interaction/complexity within crowd movements using braid entropy

Author(s):  Murat Akpulat, Murat Ekİncİ

Affiliation(s):  Kelkit Aydın Doğan Vocational School, Gümüşhane University, Gümüşhane 29100, Turkey; more

Corresponding email(s):   muratakpulat@gumushane.edu.tr, mekinci@ktu.edu.tr

Key Words:  Crowd behavior, Motion segmentation, Motion entropy, Crowd scene analysis, Complexity detection, Braid entropy

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.

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A1 - Murat Ekİncİ
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.1800313

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.




Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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