Texture-based homogeneity analysis for crowd scene modelling and abnormality detection

Jing Wang, Zhijie Xu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)


Video-based crowd behaviour analysis techniques aim at tackling challenging problems such as detecting abnormal crowd behaviours and tracking specific individuals from complex real life scenes. In this paper, an innovative spatio-temporal texture-based crowd modelling technique and its corresponding pattern analysis methods have been introduced. Through extracting and integrating those crowd textures from live or recorded videos, the so-called homogeneous random features have been deployed in the research for behavioural template matching. Experiment results have shown that the abnormality appearing in crowd scenes can be effectively and efficiently identified by using the devised methods. This new approach is envisaged to facilitate a wide spectrum of crowd analysis applications in the future through laying a solid theoretical foundation and implementation strategy for automating existing Closed-Circuit Television (CCTV)-based surveillance systems.

Original languageEnglish
Title of host publicationICAC 2014 - Proceedings of the 20th International Conference on Automation and Computing: Future Automation, Computing and Manufacturing
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781909522022
Publication statusPublished - 24 Oct 2014
Event20th International Conference on Automation and Computing - Cranfield, United Kingdom
Duration: 12 Sep 201413 Sep 2014
Conference number: 20


Conference20th International Conference on Automation and Computing
Abbreviated titleICAC 2014
Country/TerritoryUnited Kingdom


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