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.