Automated measurement of crowd density based on edge detection and optical flow

In metropolitan area, the use of analog CCTV surveillance system has steadily increased to detect and prevent crimes, terror, big persons and cars crowded in road that CCTV surveillance systems have long been employed in metropolitan area. It is necessary to equip intelligent surveillance systems, which provide an efficient solution for the problems because the cities become bigger than now in population. Therefore, a method that can efficiently measure crowd density is needed. We present an efficient method that estimates information of crowd movement by using the optical flow and the numbers of moving objects by using the numbers of edge pixels. Finally, we will classify the crowd density using the two estimated information according to five levels of crowd density.