Crowd behaviour analysis and anomaly detection by statistical modelling of flow patterns
by Saira Saleem Pathan; Ayoub Al-Hamadi; Bernd Michaelis
International Journal of Data Mining, Modelling and Management (IJDMMM), Vol. 6, No. 2, 2014

Abstract: In this paper, we investigate the crowd behaviours and localise the anomalies due to individual's abrupt dissipation. The novelty of proposed approach is described in three aspects. First, we create the spatio-temporal flow-blocks of the video sequence allowing the marginalisation of arbitrarily flow field. Second, the observed flow field in each flow-block is treated as 2D distribution of samples and mixtures of Gaussian is used to parameterise the flow field. These mixtures of Gaussian result in the distinct representation of flow field named as flow patterns for each flow-block. Third, conditional random field is employed to classify the flow patterns as normal and abnormal for each flow-block. Experiments are conducted on two challenging benchmark datasets PETS 2009 and UMN, and results show that our method achieves higher recognition rates in detecting specific and overall crowd behaviours. In addition, proposed approach shows dominating performance during the comparative analysis with similar approaches.

Online publication date: Wed, 06-Aug-2014

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Data Mining, Modelling and Management (IJDMMM):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com