Learning structured visual dictionary for object tracking

  • Authors:
  • Fan Yang;Huchuan Lu;Ming-Hsuan Yang

  • Affiliations:
  • School of Information and Communication Engineering, Dalian University of Technology, 116024 Dalian, China;School of Information and Communication Engineering, Dalian University of Technology, 116024 Dalian, China;Electrical Engineering and Computer Science, University of California at Merced, Merced, CA 95344, USA

  • Venue:
  • Image and Vision Computing
  • Year:
  • 2013

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Abstract

In this paper, we propose a visual tracking algorithm by incorporating the appearance information gathered from two collaborative feature sets and exploiting its geometric structures. A structured visual dictionary (SVD) can be learned from both appearance and geometric structure, thereby enhancing its discriminative strength between the foreground object and the background. Experimental results show that the proposed tracking algorithm using SVD (SVDTrack) performs favorably against the state-of-the-art methods.