CDES: A pixel-based crowd density estimation system for Masjid al-Haram

摘要

CDES is an automatic crowd density estimation system that can be used to estimate crowd density from digital images taken at Masjid al-Haram. Developed using a combination of image processing and artificial intelligence (AI) technologies, CDES possesses the capability to count the number of people in moderately high crowds from a flexibly selected region of interest (ROI). Background removal and edge detection are first applied to the image for crowd feature extraction. Then, the extracted crowd foreground blob pixels are scaled accordingly to correct perspective distortion. Finally, the corrected pixel blobs act as input for the backpropagation (BP) neural network to estimate the number of people within the blob. Using the area of the selected ROI, the crowd density is calculated and classified into five ranges from very low to very high. The experimental results are presented.