Flux based pedestrian flow estimation in occluded scenes

Pedestrian flow estimation is a vital issue in video surveillance. Inspired by fluid mechanics we proposed to model the pedestrian flow as time-dependent fluid, and estimate the pedestrian flow using flux. Firstly, optical flow is used to construct the motion vector field. Then, we compute the inside and outside flux components within fixed areas to estimate the pedestrian flow in different direction. In addition, we propose an edge-interval algorithm to estimate the occlusion index, which contribute to the flux. Consequently, the pedestrian flow is estimated using linear regression by combining the flux and occlusion index within a specific area. Experiments on PETS2009 and real videos, which include the occluded scenes, elucidate the good performance in pedestrian flow estimation.