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Development of a Block-Based Real-Time People Counting System

  • Hyun Hee Park
  • Hyung Gu Lee
  • Seung-In Noh
  • Jaihie Kim
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4109)

Abstract

In this paper, we propose a block-based real-time people counting system that can be used in various environments including shopping mall entrances, elevators and escalators. The main contributions of this paper are robust background subtraction, the block-based decision method and real-time processing. For robust background subtraction obtained from a number of image sequences, we used a mixture of K Gaussian. The block-based decision method was used to determine the size of the given objects (moving people) in each block. We divided the images into 72 blocks and trained the mean and variance values of the specific objects in each block. This was done in order to provide real-time processing for up to 4 channels. Finally, we analyzed various actions that can occur with moving people in real world environments.

Keywords

Training Image Shadow Region Morphological Process Counting Line Counting Crowd 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Thou-Ho, C.: An automatic bi-directional passing-people counting method based on color image processing. In: Proceedings of the IEEE 37th Annual 2003 International Carnahan Conference on Security Technology, October 14-16, pp. 200–207 (2003)Google Scholar
  2. 2.
    Terada, K., Yamaguchi, J.: A System for Counting Passing People by Using the Color Camera. The Transactions of The Institute of Electrical Engineers of JapanGoogle Scholar
  3. 3.
    Terada, K., Yoshida, D., Oe, S., Yamaguchi, J.: A Method of Counting the Passing People by Using the Stereo Images. In: Proceedings of the 1999 International Conference on Image Processing, ICIP 1999, October 24-28, vol. 2, pp. 338–342 (1999)Google Scholar
  4. 4.
    Segen, J.: A camera-based system for tracking people in real time. In: Proceedings of the 13th International Conference on Pattern Recognition, August 25-29, vol. 3, pp. 63–67 (1996)Google Scholar
  5. 5.
    Rossi, M., Bozzoli, A.: Tracking and counting moving people. In: Proceedings of the IEEE International Conference on Image Processing, ICIP 1994, November 13-16, vol. 3, pp. 212–216 (1994)Google Scholar
  6. 6.
    Zang, Q., Klette, R.: Robust background subtraction and maintenance. In: Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004, August 23-26, vol. 2, pp. 90–93 (2004)Google Scholar
  7. 7.
    Wang, H., Suter, D.: A re-evaluation of mixture of Gaussian background modeling [video signal processing applications]. In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005 (ICASSP 2005), March 18-23, vol. 2, pp. ii/1017–ii/1020 (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Hyun Hee Park
    • 1
  • Hyung Gu Lee
    • 1
  • Seung-In Noh
    • 2
  • Jaihie Kim
    • 1
  1. 1.Department of Electrical and Electronic EngineeringYonsei University, Biometrics Engineering Research Center(BERC)Republic of Korea
  2. 2.Samsung ElectronicsSuwon-city, Gyeonggi-doRepublic of Korea

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