Abstract
In this paper, we present a new people counting method based on universities’ surveillance videos. Firstly, we set the threshold value for the HSV space V channel pixel-based on the color of hair so as to detect the head regions. Secondly, we fit the function of the head size and space coordinate and then remove the connected regions which are too big or too small. Finally, we detect the motion using the improved frame difference method and remove the static regions. This method has solved the problems of that the feature is not obvious when students are in different positions with different sizes due to the perspective effect of cameras. There is false detection due to the interference of static entities such as bags and basketballs on tables and chairs. Experimental results show that the average correct detecting rate can reach 87.71%. By calculating, the detected classroom occupancy rate and the actual classroom occupancy rate are almost at the same.
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Liu, Y., Wu, H. (2014). A People Counting Method Based on Universities’ Surveillance Videos and Its Application on Classroom Query. In: Sun, Z., Shan, S., Sang, H., Zhou, J., Wang, Y., Yuan, W. (eds) Biometric Recognition. CCBR 2014. Lecture Notes in Computer Science, vol 8833. Springer, Cham. https://doi.org/10.1007/978-3-319-12484-1_55
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DOI: https://doi.org/10.1007/978-3-319-12484-1_55
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-12483-4
Online ISBN: 978-3-319-12484-1
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