Recent review of crowd anomaly detection

Junjie Ma; Yaping Dai; Kaoru Hirota; Xiangyang Liu; Guosai Yang

Recent review of crowd anomaly detection

Junjie Ma, Yaping Dai, Kaoru Hirota, Xiangyang Liu, Guosai Yang

School of Automation

Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

With the population and crowd activities increased, large-scale crowd events make the probability of hazard incidents larger than ever. In the past decades, automated crowd scene analysis has been of great interest in computer vision. As a key aspect of crowd scene analysis, a number of work on video-based crowd anomaly detection in dense scenes have been proposed. This article presents a survey on crowd analysis in dense crowd scenes using computer vision techniques, covering two aspects: crowd density estimation and abnormal event detection. Some existing problems and perspectives are also discussed at the end.

Original language	English
Title of host publication	ISCIIA 2016 - 7th International Symposium on Computational Intelligence and Industrial Applications
Publisher	Fuji Technology Press
ISBN (Electronic)	9784990534349
Publication status	Published - 2016
Event	7th International Symposium on Computational Intelligence and Industrial Applications, ISCIIA 2016 - Beijing, China Duration: 3 Nov 2016 → 6 Nov 2016

Publication series

Name	ISCIIA 2016 - 7th International Symposium on Computational Intelligence and Industrial Applications

Conference

Conference	7th International Symposium on Computational Intelligence and Industrial Applications, ISCIIA 2016
Country/Territory	China
City	Beijing
Period	3/11/16 → 6/11/16

Keywords

Abnormal event detection
Crowd anomaly detection
Crowd density estimation
Dense crowd scenes
Review

Cite this

@inproceedings{68edacb6b58740c0a5b2a2ed383403ed,

title = "Recent review of crowd anomaly detection",

abstract = "With the population and crowd activities increased, large-scale crowd events make the probability of hazard incidents larger than ever. In the past decades, automated crowd scene analysis has been of great interest in computer vision. As a key aspect of crowd scene analysis, a number of work on video-based crowd anomaly detection in dense scenes have been proposed. This article presents a survey on crowd analysis in dense crowd scenes using computer vision techniques, covering two aspects: crowd density estimation and abnormal event detection. Some existing problems and perspectives are also discussed at the end.",

keywords = "Abnormal event detection, Crowd anomaly detection, Crowd density estimation, Dense crowd scenes, Review",

author = "Junjie Ma and Yaping Dai and Kaoru Hirota and Xiangyang Liu and Guosai Yang",

note = "Publisher Copyright: {\textcopyright} 2016, Fuji Technology Press. All rights reserved.; 7th International Symposium on Computational Intelligence and Industrial Applications, ISCIIA 2016 ; Conference date: 03-11-2016 Through 06-11-2016",

year = "2016",

language = "English",

series = "ISCIIA 2016 - 7th International Symposium on Computational Intelligence and Industrial Applications",

publisher = "Fuji Technology Press",

booktitle = "ISCIIA 2016 - 7th International Symposium on Computational Intelligence and Industrial Applications",

address = "Japan",

}

Ma, J, Dai, Y , Hirota, K, Liu, X & Yang, G 2016, Recent review of crowd anomaly detection. in ISCIIA 2016 - 7th International Symposium on Computational Intelligence and Industrial Applications. ISCIIA 2016 - 7th International Symposium on Computational Intelligence and Industrial Applications, Fuji Technology Press, 7th International Symposium on Computational Intelligence and Industrial Applications, ISCIIA 2016, Beijing, China, 3/11/16.

Recent review of crowd anomaly detection. / Ma, Junjie; Dai, Yaping ; Hirota, Kaoru et al.
ISCIIA 2016 - 7th International Symposium on Computational Intelligence and Industrial Applications. Fuji Technology Press, 2016. (ISCIIA 2016 - 7th International Symposium on Computational Intelligence and Industrial Applications).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Recent review of crowd anomaly detection

AU - Ma, Junjie

AU - Dai, Yaping

AU - Hirota, Kaoru

AU - Liu, Xiangyang

AU - Yang, Guosai

PY - 2016

Y1 - 2016

N2 - With the population and crowd activities increased, large-scale crowd events make the probability of hazard incidents larger than ever. In the past decades, automated crowd scene analysis has been of great interest in computer vision. As a key aspect of crowd scene analysis, a number of work on video-based crowd anomaly detection in dense scenes have been proposed. This article presents a survey on crowd analysis in dense crowd scenes using computer vision techniques, covering two aspects: crowd density estimation and abnormal event detection. Some existing problems and perspectives are also discussed at the end.

AB - With the population and crowd activities increased, large-scale crowd events make the probability of hazard incidents larger than ever. In the past decades, automated crowd scene analysis has been of great interest in computer vision. As a key aspect of crowd scene analysis, a number of work on video-based crowd anomaly detection in dense scenes have been proposed. This article presents a survey on crowd analysis in dense crowd scenes using computer vision techniques, covering two aspects: crowd density estimation and abnormal event detection. Some existing problems and perspectives are also discussed at the end.

KW - Abnormal event detection

KW - Crowd anomaly detection

KW - Crowd density estimation

KW - Dense crowd scenes

KW - Review

UR - http://www.scopus.com/inward/record.url?scp=84997701264&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84997701264

T3 - ISCIIA 2016 - 7th International Symposium on Computational Intelligence and Industrial Applications

BT - ISCIIA 2016 - 7th International Symposium on Computational Intelligence and Industrial Applications

PB - Fuji Technology Press

T2 - 7th International Symposium on Computational Intelligence and Industrial Applications, ISCIIA 2016

Y2 - 3 November 2016 through 6 November 2016

ER -

Recent review of crowd anomaly detection

Abstract

Publication series

Conference

Keywords

Other files and links

Fingerprint

Cite this