@inproceedings{f332cacfd66b4bd3b4757b44d7b481a8,
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, Spatio-temporal volume, Texture model",
author = "Jing Wang and Zhijie Xu and Yanlong Cao and Yuanping Xu",
note = "Publisher Copyright: {\textcopyright} 2017 Chinese Automation and Computing Society in the UK - CACSUK.; 23rd IEEE International Conference on Automation and Computing, ICAC 2017 ; Conference date: 07-09-2017 Through 08-09-2017",
year = "2017",
month = oct,
day = "23",
doi = "10.23919/IConAC.2017.8082022",
language = "English",
series = "ICAC 2017 - 2017 23rd IEEE International Conference on Automation and Computing: Addressing Global Challenges through Automation and Computing",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Jie Zhang",
booktitle = "ICAC 2017 - 2017 23rd IEEE International Conference on Automation and Computing",
}