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.
|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|
|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||23rd International Conference on Automation and Computing|
|Abbreviated title||ICAC 2017|
|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.|
Wang, J., Xu, Z., Cao, Y. L., & 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..