Spatial-temporal affinity propagation for feature clustering with application to traffic video analysis

Abstract

In this paper, we propose STAP (Spatial-Temporal Affinity Propagation), an extension of the Affinity Propagation algorithm for feature points clustering, by incorporating temporal consistency of the clustering configurations between consecutive frames. By extending AP to the temporal domain, STAP successfully models the smooth-motion assumption in object detection and tracking. Our experiments on applications in traffic video analysis demonstrate the effectiveness and efficiency of the proposed method and its advantages over existing approaches. © 2011 Springer-Verlag Berlin Heidelberg.