Network Flow Based Collective Behavior Analysis

With the large-scale activities increasing gradually, the intelligent video surveillance system becomes more and more popular and important. The trajectory identification and behavior analysis are very important techniques for the intelligent video surveillance system. This paper focuses on the trajectory identification and behavior analysis framework for video surveillance system. The framework is implemented on footbridge video and queuing video of Shanghai World Expo 2010 video surveillance system. The experimental results show the efficiency of our proposed framework.

[1]  John Anderson,et al.  Wireless sensor networks for habitat monitoring , 2002, WSNA '02.

[2]  Mónica F. Bugallo,et al.  Target Tracking by Particle Filtering in Binary Sensor Networks , 2008, IEEE Transactions on Signal Processing.

[3]  Hai Tao,et al.  Counting Pedestrians in Crowds Using Viewpoint Invariant Training , 2005, BMVC.

[4]  Norbert Brändle,et al.  Pedestrian Detection and Tracking for Counting Applications in Crowded Situations , 2006, 2006 IEEE International Conference on Video and Signal Based Surveillance.

[5]  Upamanyu Madhow,et al.  Multiple-Target Tracking With Binary Proximity Sensors , 2011, TOSN.

[6]  Luc Van Gool,et al.  You'll never walk alone: Modeling social behavior for multi-target tracking , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[7]  Xing Xie,et al.  Mining interesting locations and travel sequences from GPS trajectories , 2009, WWW '09.

[8]  Longbing Cao,et al.  In-depth behavior understanding and use: The behavior informatics approach , 2010, Inf. Sci..

[9]  Dino Pedreschi,et al.  Trajectory pattern mining , 2007, KDD '07.

[10]  Luc Van Gool,et al.  Coupled Object Detection and Tracking from Static Cameras and Moving Vehicles , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.