Foreground extraction for real-time crowd analytics in surveillance system

In this paper, we propose an adaptive background modeling algorithm for crowd surveillance system. We employed Approximate Median Method (AMM) along with the Phase congruency edge detector to develop the background model. The resulting foreground of the proposed model was obtained by applying a logical AND operation between binary maps of the (foreground) of the AMM image and the gradient information of the (Phase congruency edge detector) PC. Experimental results demonstrate that the proposed method is highly accurate while providing a processing speed of 24.8 fps allowing its implementation for real time application.