Publications

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Search for Publication


Year(s) from:  to 
Author:
Keywords (separated by spaces):

Modeling and Recognition of Human Actions Using a Stochastic Approach

E. Koller-Meier and L. Van Gool
Proceedings of the 2nd European Workshop on Advanced Video-Based Surveillance Systems 2001 (AVBS'01)
London, UK, September 2001

Abstract

This paper describes a self-learning prototype system for the real-time detection of unusual motion patterns. The proposed surveillance system uses a three-step approach consisting of a tracking, a learning and a recognition part. In the first step, an arbitrary, changing number of objects are tracked with an extension of the Condensation algorithm. From the history of the tracked object states, temporal trajectories are formed which describe the motion paths of these objects. Secondly, characteristic motion patterns are learned by clustering these trajectories into prototype curves. In the final step, motion recognition is then tackled by tracking the position within these prototype curves based on the same method, the extended Condensation algorithm, used for the object tracking.


Download in postscript format
@InProceedings{eth_biwi_00221,
  author = {E. Koller-Meier and L. Van Gool},
  title = {Modeling and Recognition of Human Actions Using a Stochastic Approach},
  booktitle = {Proceedings of the 2nd European Workshop on Advanced Video-Based Surveillance Systems 2001 (AVBS'01)},
  year = {2001},
  month = {September},
  pages = {17--28},
  keywords = {tracking, condensation, human motion recognition, spatio-temporal grouping}
}