People counting across spatially disjoint cameras by flow estimation between foreground regions

Our goal is to develop a method for counting the number of people traveling over a wide area monitored by spatially disjoint multiple cameras with non-overlapping fields of view. The proposed method counts the number of people traversing across each pair of cameras´ fields of view by estimating the flows between the foreground regions which have disappeared from and appeared in the camera views within a short time interval. The approach aims at resolving two problems: people in a foreground region can split and merge outside the cameras´ fields of view, and the appearance variance of the same person and persons with similar appearance can lead to errors in person re-identification across cameras. The average errors of 0.184 persons in counting the number of people traveling over an area in a university campus monitored by four virtual cameras for 100 minutes have demonstrated the effectiveness of the proposed method.