An Approach to Event Recognition for Visual Surveillance Systems

In this paper, we propose a new vision based method to recognize the entering and exiting events from video sequences via motion analysis. Without sensors, the proposed approach is invariant to body shape and clothing as a combination of edge detection, motion history image and geometrical characteristic of the human shape in MHI sequences. The proposed method includes several applications such as access control in visual surveillance and computer vision fields.

[1]  Jesse Hoey,et al.  Automated Detection of Unusual Events on Stairs , 2006, The 3rd Canadian Conference on Computer and Robot Vision (CRV'06).

[2]  Mubarak Shah,et al.  Monitoring human behavior from video taken in an office environment , 2001, Image Vis. Comput..

[3]  Jean Meunier,et al.  Fall Detection from Human Shape and Motion History Using Video Surveillance , 2007, 21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07).

[4]  Michael Spann,et al.  Event detection for intelligent car park video surveillance , 2005, Real Time Imaging.

[5]  Mubarak Shah,et al.  Recognizing human actions in a static room , 1998, Proceedings Fourth IEEE Workshop on Applications of Computer Vision. WACV'98 (Cat. No.98EX201).

[6]  James W. Davis,et al.  The Recognition of Human Movement Using Temporal Templates , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Yap-Peng Tan,et al.  Fall Incidents Detection for Intelligent Video Surveillance , 2005, 2005 5th International Conference on Information Communications & Signal Processing.

[8]  Osama Masoud,et al.  A method for human action recognition , 2003, Image Vis. Comput..

[9]  Tieniu Tan,et al.  A survey on visual surveillance of object motion and behaviors , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).