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A block-based real-time people counting system  

Park Hyun-Hee (Biometrics Engineering Research Center, Yonsei Univ.)
Lee Hyung-Gu (Biometrics Engineering Research Center, Yonsei Univ.)
Kim Jai-Hie (Biometrics Engineering Research Center, Yonsei Univ.)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.43, no.5, 2006 , pp. 22-29 More about this Journal
Abstract
In this paper, we propose a block-based real-time people counting system that can be used in various environments including showing 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 $6{\times}12$ 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
People Counting System; Mixture of Gaussian; Real-time; 4 Channels;
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