Crowd Analysis at Mass Transit Sites

We propose a novel method for detecting and estimating the count of people in groups, dense or otherwise, as well as tracking them. Using prior knowledge obtained from the scene and accurate camera calibration, the system learns the parameters required for estimation. This information can then be used to estimate the count of people in the scene, in realtime. There are no constraints on camera placement. Groups are tracked in the same manner as individuals, using Kalman filtering techniques. Results are provided for groups of various sizes moving in an unconstrained fashion in crowded scenes

[1]  Alex Pentland,et al.  Pfinder: Real-Time Tracking of the Human Body , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Larry S. Davis,et al.  W4S : A real-time system for detecting and tracking people in 2 D , 1998, eccv 1998.

[3]  Sergio A. Velastin,et al.  Crowd monitoring using image processing , 1995 .

[4]  Luciano da Fontoura Costa,et al.  Automatic estimation of crowd density using texture , 1998 .

[5]  Ramakant Nevatia,et al.  Bayesian human segmentation in crowded situations , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[6]  N. Papanikolopoulos,et al.  Practical mixtures of Gaussians with brightness monitoring , 2004, Proceedings. The 7th International IEEE Conference on Intelligent Transportation Systems (IEEE Cat. No.04TH8749).

[7]  Osama Masoud,et al.  Using geometric primitives to calibrate traffic scenes , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[8]  Larry S. Davis,et al.  Hydra: multiple people detection and tracking using silhouettes , 1999, Proceedings 10th International Conference on Image Analysis and Processing.

[9]  Larry S. Davis,et al.  W/sup 4/: A Real Time System for Detecting and Tracking People , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[10]  Ramakant Nevatia,et al.  Tracking multiple humans in complex situations , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Osama Masoud,et al.  A novel method for tracking and counting pedestrians in real-time using a single camera , 2001, IEEE Trans. Veh. Technol..