Open Science Research Excellence
@article{(International Science Index):http://waset.org/publications/8192,
  title    = {A Robust Visual Tracking Algorithm with Low-Rank Region Covariance},
  author    = {Songtao Wu and  Yuesheng Zhu and  Ziqiang Sun},
  country   = {},
  institution={},
  abstract  = {Region covariance (RC) descriptor is an effective
and efficient feature for visual tracking. Current RC-based tracking
algorithms use the whole RC matrix to track the target in video
directly. However, there exist some issues for these whole RCbased
algorithms. If some features are contaminated, the whole RC
will become unreliable, which results in lost object-tracking. In
addition, if some features are very discriminative to the
background, other features are still processed and thus reduce the
efficiency. In this paper a new robust tracking method is proposed,
in which the whole RC matrix is decomposed into several low rank
matrices. Those matrices are dynamically chosen and processed so
as to achieve a good tradeoff between discriminability and
complexity. Experimental results have shown that our method is
more robust to complex environment changes, especially either
when occlusion happens or when the background is similar to the
target compared to other RC-based methods.},
    journal   = {International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering},  volume    = {5},
  number    = {7},
  year      = {2011},
  pages     = {850 - 855},
  ee        = {http://waset.org/publications/8192},
  url       = {http://waset.org/Publications?p=55},
  bibsource = {http://waset.org/Publications},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 55, 2011},
}