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.
|Title of host publication
|ICAC 2014 - Proceedings of the 20th International Conference on Automation and Computing: Future Automation, Computing and Manufacturing
|Institute of Electrical and Electronics Engineers Inc.
|Number of pages
|Published - 24 Oct 2014
|20th International Conference on Automation and Computing - Cranfield, United Kingdom
Duration: 12 Sep 2014 → 13 Sep 2014
Conference number: 20
|20th International Conference on Automation and Computing
|12/09/14 → 13/09/14