Robust visual tracking via augmented kernel SVM

@article{Bai2014RobustVT,
  title={Robust visual tracking via augmented kernel SVM},
  author={Yancheng Bai and Ming Tang},
  journal={Image Vision Comput.},
  year={2014},
  volume={32},
  pages={465-475}
}
Most current tracking approaches utilize only one type of feature to represent the target and learn the appearance model of the target just using the current frame or a few recent ones. The limited representation of one single type of feature might not represent the target well. What’s more, the appearance model learning from the current frame or a few recent ones is intolerant of abrupt appearance changes in short time intervals. These two factors might cause the track’s failure. To overcome… CONTINUE READING
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