Determination of Object Directions Using Optical Flow for Crowd Monitoring

Abstract

Determination of object direction in a multi-camera tracking system is critical. The absence of object direction from other cameras pose challenges if the object is along the optical axis. The problem of determining object direction worsens further if the cameras in the existing infrastructure are improperly placed and are uncontrollable. To determine the direction of an object in such situations, three methods based on optical flow (OF) are presented. The first method uses centroids of optical flow vector magnitudes and Kalman filter for tracking and is suitable for less crowded scenarios. The second method uses geometric moments to evaluate the flow vector distribution and to ascertain the direction in case of crowded scenarios by partitioning the scene and then applying moments to individual partitions independently. The third method is appropriate for small-sized objects near vanishing points where global object motion is less. During surveillance, whether multi-object, single-object or crowded scenarios, the aforementioned methods are applicable accordingly. The results show that the object directions can be accurately inferred from three methods for different scenarios.