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

Authors:
Jun Yang;Yang Wang;Arcot Sowmya;Jie Xu;Zhidong Li;Bang Zhang
Affiliations:
School of Computer Science and Engineering, The University of New South Wales and National ICT Australia;School of Computer Science and Engineering, The University of New South Wales and National ICT Australia;School of Computer Science and Engineering, The University of New South Wales;School of Computer Science and Engineering, The University of New South Wales and National ICT Australia;School of Computer Science and Engineering, The University of New South Wales and National ICT Australia;School of Computer Science and Engineering, The University of New South Wales and National ICT Australia
Venue:
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part II
Year:
2010

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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.