Detection of anomalous crowd behaviour using hyperspherical clustering

Rao, Aravinda S., Gubbi, Jayavardhana, Rajasegarar, Sutharshan, Marusic, Slaven and Palaniswami, Marimuthu 2014, Detection of anomalous crowd behaviour using hyperspherical clustering, in DICTA 2014 : Proceedings of the Digital Image Computing : Techniques and Applications International Conference, IEEE, Piscataway, N.J., doi: 10.1109/DICTA.2014.7008100.

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Title Detection of anomalous crowd behaviour using hyperspherical clustering
Author(s) Rao, Aravinda S.
Gubbi, Jayavardhana
Rajasegarar, SutharshanORCID iD for Rajasegarar, Sutharshan
Marusic, Slaven
Palaniswami, Marimuthu
Conference name Digital lmage Computing : Techniques and Applications. Conference (2014 : Wollongong, New South Wales)
Conference location Wollongong, New South Wales
Conference dates 25-27 Nov. 2014
Title of proceedings DICTA 2014 : Proceedings of the Digital Image Computing : Techniques and Applications International Conference
Publication date 2014
Publisher IEEE
Place of publication Piscataway, N.J.
Summary Analysis of crowd behaviour in public places is an indispensable tool for video surveillance. Automated detection of anomalous crowd behaviour is a critical problem with the increase in human population. Anomalous events may include a person loitering about a place for unusual amounts of time; people running and causing panic; the size of a group of people growing over time etc. In this work, to detect anomalous events and objects, two types of feature coding has been proposed: spatial features and spatio-temporal features. Spatial features comprises of contrast, correlation, energy and homogeneity, which are derived from Gray Level Co-occurrence Matrix (GLCM). Spatio-temporal feature includes the time spent by an object at different locations in the scene. Hyperspherical clustering has been employed to detect the anomalies. Spatial features revealed the anomalous frames by using contrast and homogeneity measures. Loitering behaviour of the people were detected as anomalous objects using the spatio-temporal coding.
ISBN 9781479954094
Language eng
DOI 10.1109/DICTA.2014.7008100
Field of Research 080106 Image Processing
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1.1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2014, IEEE
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