Wavelet-based Texture Model for Crowd Dynamic Analysis

Jing Wang; Zhijie Xu; Yan long Cao; Yuanping Xu

doi:10.23919/IConAC.2017.8082022

Wavelet-based Texture Model for Crowd Dynamic Analysis

Jing Wang, Zhijie Xu, Yan long Cao, Yuanping Xu

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

1 Citation (Scopus)

Abstract

Crowd event detection techniques aim at solving real-world surveillance problems, such as detecting crowd anomaly and tracking specific person in a highly dynamic crowd scene. In this paper, we proposed an innovate texture-based analysis method to model crowd dynamics and us it to distinguish the crowd behaviours. To describe complicated crowd scenes, homogeneous random features have been deployed in the research for behavioural template matching. Experiment results have shown that the anomaly appearing in crowd scenes can be effectively and efficiently identified by using the devised methods.

Original language	English
Title of host publication	Proceedings of the 23rd International Conference on Automation & Computing, (University of Huddersfield, 7-8 September 2017)
Publisher	Institute of Electrical and Electronics Engineers Inc.
Number of pages	5
ISBN (Electronic)	9780701702601
ISBN (Print)	9781509050406
DOIs	https://doi.org/10.23919/IConAC.2017.8082022
Publication status	Published - 26 Oct 2017
Event	23rd International Conference on Automation and Computing: Addressing Global Challenges through Automation and Computing - University of Huddersfield, Huddersfield, United Kingdom Duration: 7 Sep 2017 → 8 Sep 2017 Conference number: 23 https://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=41042 (Link to Conference Website)

Conference

Conference	23rd International Conference on Automation and Computing
Abbreviated title	ICAC 2017
Country/Territory	United Kingdom
City	Huddersfield
Period	7/09/17 → 8/09/17
Other	The scope of the conference covers a broad spectrum of areas with multi-disciplinary interests in the fields of automation, control engineering, computing and information systems, ranging from fundamental research to real-world applications.
Internet address	https://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=41042 (Link to Conference Website)

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http://eprints.hud.ac.uk/id/eprint/33567Licence: Unspecified

Cite this

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title = "Wavelet-based Texture Model for Crowd Dynamic Analysis",

abstract = "Crowd event detection techniques aim at solving real-world surveillance problems, such as detecting crowd anomaly and tracking specific person in a highly dynamic crowd scene. In this paper, we proposed an innovate texture-based analysis method to model crowd dynamics and us it to distinguish the crowd behaviours. To describe complicated crowd scenes, homogeneous random features have been deployed in the research for behavioural template matching. Experiment results have shown that the anomaly appearing in crowd scenes can be effectively and efficiently identified by using the devised methods.",

keywords = "Component, Crowd dynamics, Texture model, Spatio-temporal volume",

author = "Jing Wang and Zhijie Xu and Cao, {Yan long} and Yuanping Xu",

note = "“{\textcopyright} {\textcopyright} 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”; 23rd International Conference on Automation and Computing : Addressing Global Challenges through Automation and Computing, ICAC 2017 ; Conference date: 07-09-2017 Through 08-09-2017",

year = "2017",

month = oct,

day = "26",

doi = "10.23919/IConAC.2017.8082022",

language = "English",

isbn = "9781509050406",

booktitle = "Proceedings of the 23rd International Conference on Automation & Computing, (University of Huddersfield, 7-8 September 2017)",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

url = "https://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=41042",

}

Wang, J, Xu, Z, Cao, YL & Xu, Y 2017, Wavelet-based Texture Model for Crowd Dynamic Analysis. in Proceedings of the 23rd International Conference on Automation & Computing, (University of Huddersfield, 7-8 September 2017). Institute of Electrical and Electronics Engineers Inc., 23rd International Conference on Automation and Computing, Huddersfield, United Kingdom, 7/09/17. https://doi.org/10.23919/IConAC.2017.8082022

Wavelet-based Texture Model for Crowd Dynamic Analysis. / Wang, Jing; Xu, Zhijie; Cao, Yan long et al.

Proceedings of the 23rd International Conference on Automation & Computing, (University of Huddersfield, 7-8 September 2017). Institute of Electrical and Electronics Engineers Inc., 2017.

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

TY - GEN

T1 - Wavelet-based Texture Model for Crowd Dynamic Analysis

AU - Wang, Jing

AU - Xu, Zhijie

AU - Cao, Yan long

AU - Xu, Yuanping

N1 - Conference code: 23

PY - 2017/10/26

Y1 - 2017/10/26

N2 - Crowd event detection techniques aim at solving real-world surveillance problems, such as detecting crowd anomaly and tracking specific person in a highly dynamic crowd scene. In this paper, we proposed an innovate texture-based analysis method to model crowd dynamics and us it to distinguish the crowd behaviours. To describe complicated crowd scenes, homogeneous random features have been deployed in the research for behavioural template matching. Experiment results have shown that the anomaly appearing in crowd scenes can be effectively and efficiently identified by using the devised methods.

AB - Crowd event detection techniques aim at solving real-world surveillance problems, such as detecting crowd anomaly and tracking specific person in a highly dynamic crowd scene. In this paper, we proposed an innovate texture-based analysis method to model crowd dynamics and us it to distinguish the crowd behaviours. To describe complicated crowd scenes, homogeneous random features have been deployed in the research for behavioural template matching. Experiment results have shown that the anomaly appearing in crowd scenes can be effectively and efficiently identified by using the devised methods.

KW - Component

KW - Crowd dynamics

KW - Texture model

KW - Spatio-temporal volume

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U2 - 10.23919/IConAC.2017.8082022

DO - 10.23919/IConAC.2017.8082022

M3 - Conference contribution

SN - 9781509050406

BT - Proceedings of the 23rd International Conference on Automation & Computing, (University of Huddersfield, 7-8 September 2017)

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 23rd International Conference on Automation and Computing

Y2 - 7 September 2017 through 8 September 2017

ER -

Wavelet-based Texture Model for Crowd Dynamic Analysis

Abstract

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