By Topic

Dynamic human crowd modeling and its application to anomalous events detcetion

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Duan-Yu Chen ; Dept. of Electr. Eng., Yuan-Ze Univ., Chungli, Taiwan ; Po-Chung Huang

Analyzing human crowds is an important issue in video surveillance and is a challenging task due to their nature of non-rigid shapes. In this paper, optical flows are first estimated and then used for a clue to cluster human crowds into groups in unsupervised manner using our proposed clustering method. While the clusters of human crowds are obtained, their behaviors with attributes, orientation, position and crowd size, are characterized by a model of force field. Finally, we can predict the behaviors of human crowds based on the model and then detect if any anomalies of human crowd(s) present in the scene. Experiment results obtained by using extensive dataset show that our system is effective and efficient in detect anomalous events for uncontrolled environment of surveillance videos.

Published in:

Multimedia and Expo (ICME), 2010 IEEE International Conference on

Date of Conference:

19-23 July 2010