Visual Tracking Using Sparsity Induced Similarity

  • Authors:
  • Huaping Liu;Fuchun Sun

  • Affiliations:
  • -;-

  • Venue:
  • ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
  • Year:
  • 2010

Quantified Score

Hi-index 0.01

Visualization

Abstract

Currently sparse signal reconstruction gains considerable interests and is applied in many fields. In this paper, we propose a new approach which utilizes the sparsity induced similarity to construct the tracking algorithm. Compared with state-of-the-art, the advantage of this approach is that the sparse representation needs to be calculated for only once and therefore the time cost is dramatically decreased. In addition, extensive experimental comparisons show that the proposed approach is more robust than some existing approaches.