A method for counting people attending large public events

The algorithm for people counting in crowded scenes, based on the idea of virtual gate which uses optical flow method is presented. The concept and practical application of the developed algorithm under real conditions is depicted. The aim of the work is to estimate the number of people passing through entrances of a large sport hall. The most challenging problem was the unpredicted behavior of people while entering the building. The examined flow of people fluctuated between individual persons and dense crowd. A series of experiments during sport and entertainment events was made. The results of the experiments show a high efficiency of the elaborated algorithm.

[1]  Piotr Szczuko,et al.  Genetic programming extension to APF-based monocular human body pose estimation , 2012, Multimedia Tools and Applications.

[2]  Moving Object Detection and Tracking for the Purpose of Multimodal Surveillance System in Urban Areas , 2008, New Directions in Intelligent Interactive Multimedia.

[3]  Antonio Albiol,et al.  Real-time high density people counter using morphological tools , 2001, IEEE Trans. Intell. Transp. Syst..

[4]  Ryosuke Shibasaki,et al.  Laser-based detection and tracking of multiple people in crowds , 2007, Comput. Vis. Image Underst..

[5]  Lakhmi C. Jain,et al.  New Directions in Intelligent Interactive Multimedia , 2008, New Directions in Intelligent Interactive Multimedia.

[6]  Axel Poigné,et al.  Evaluation of a "Smart" Pedestrian Counting System Based on Echo State Networks , 2009, EURASIP J. Embed. Syst..

[7]  Henryk Krawczyk,et al.  The Task Graph Assignment for KASKADA Platform , 2010, ICSOFT.

[8]  Luigi Cinque,et al.  A Statistical Method for People Counting in Crowded Environments , 2007, 14th International Conference on Image Analysis and Processing (ICIAP 2007).

[9]  Naim Dahnoun,et al.  Studies in Computational Intelligence , 2013 .

[10]  Andrzej Czyzewski,et al.  Detection and localization of selected acoustic events in acoustic field for smart surveillance applications , 2012, Multimedia Tools and Applications.

[11]  Leonidas J. Guibas,et al.  Counting people in crowds with a real-time network of simple image sensors , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[12]  Jong Seok Lim,et al.  Detecting and tracking of multiple pedestrians using motion, color information and the AdaBoost algorithm , 2012, Multimedia Tools and Applications.

[13]  Robert T. Collins,et al.  Marked point processes for crowd counting , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[14]  Gunnar Farnebäck,et al.  Two-Frame Motion Estimation Based on Polynomial Expansion , 2003, SCIA.

[15]  A. A. Knecht.  EVALUATION OF A , 1972 .

[16]  Antonio Albiol,et al.  Statistical video analysis for crowds counting , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[17]  Mustafa Cenk Gursoy,et al.  Distributed wide-area multi-object tracking with non-overlapping camera views , 2011, 2011 IEEE International Conference on Multimedia and Expo.

[18]  Andrzej Czyzewski,et al.  Detection and localization of selected acoustic events in acoustic field for smart surveillance applications , 2011, Multimedia Tools and Applications.