A Cost-Effective People-Counter for a Crowd of Moving People Based on Two-Stage Segmentation

This paper is dedicated to a cost-effective people counter for a crowd of moving people by using a zenithal video camera. To obtain a more accurate people count, the two-stage segmentation is developed for extracting each person from a crowd. Firstly, a crowd is segmented by frame-difference technique, followed by morphological processing and region growing. Then, the connected-component labeling method is used to generate many individual people-patterns from the segmented crowd. People-image features, such as the area, height, and width of each people-pattern, are analyzed in order to correctly segment each person from each individual people-pattern. Finally, each person segmented is tracked till touching the base-line and then is counted. Experimental results show that the counting accuracy can be achieved above 91% on average if the crowd moves normally. A comparison with other reported methods of using a zenithal camera manifests the superiority of the proposed method in counting accuracy.

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

[2]  Osama Masoud,et al.  Robust pedestrian tracking using a model-based approach , 1997, Proceedings of Conference on Intelligent Transportation Systems.

[3]  Kenji Terada,et al.  A method of counting the passing people by using the stereo images , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[4]  F Bartolini,et al.  Counting people getting in and out of a bus by real-time image-sequence processing , 1994, Image Vis. Comput..

[5]  Christoph Bregler,et al.  Learning and recognizing human dynamics in video sequences , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[6]  Ramin Zabih,et al.  Counting people from multiple cameras , 1999, Proceedings IEEE International Conference on Multimedia Computing and Systems.

[7]  Hans-Hellmut Nagel,et al.  Tracking Persons in Monocular Image Sequences , 1999, Comput. Vis. Image Underst..

[8]  Tsong-Yi Chen,et al.  Multipath Flatted-Hexagon Search for Block Motion Estimation , 2010, J. Inf. Hiding Multim. Signal Process..

[9]  Luc Duvieubourg,et al.  Linear image sequence analysis for passengers counting in public transport , 1996 .

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

[11]  Chao-Ho Chen,et al.  People Recognition for Entering and Leaving a Video Surveillance Area , 2010, J. Softw..

[12]  Yung-Chuen Chiou,et al.  A REAL-TIME VIDEO OBJECT SEGMENTATION ALGORITHM BASED ON CHANGE DETECTION AND BACKGROUND UPDATING , 2005 .

[13]  Narciso García,et al.  DCT based segmentation applied to a scalable zenithal people counter , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[14]  M. Rossi,et al.  Tracking and counting moving people , 1994, Proceedings of 1st International Conference on Image Processing.

[15]  Xiaowei Zhang,et al.  Automatic human head location for pedestrian counting , 1997 .

[16]  Tsong-Yi Chen,et al.  People Counting System for Getting In/Out of a Bus Based on Video Processing , 2008, 2008 Eighth International Conference on Intelligent Systems Design and Applications.

[17]  Wu-Chih Hu,et al.  Feature-based Face Detection Against Skin-color Like Backgrounds with Varying Illumination , 2011, J. Inf. Hiding Multim. Signal Process..

[18]  Christian Wöhler,et al.  Motion-based recognition of pedestrians , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[19]  Jake K. Aggarwal,et al.  Human Motion Analysis: A Review , 1999, Comput. Vis. Image Underst..

[20]  Trevor Darrell,et al.  Integrated Person Tracking Using Stereo, Color, and Pattern Detection , 2000, International Journal of Computer Vision.

[21]  Sung-Jea Ko,et al.  Real-time Vision-based People Counting System for the Security Door , 2002 .