Discriminative Bag-of-Words-Based Adaptive Appearance Model for Robust Visual Tracking

@article{Zeng2017DiscriminativeBA,
  title={Discriminative Bag-of-Words-Based Adaptive Appearance Model for Robust Visual Tracking},
  author={Fanxiang Zeng and Zhitong Huang and Yuefeng Ji},
  journal={IEEE Signal Processing Letters},
  year={2017},
  volume={24},
  pages={907-911}
}
In this letter, we propose a novel discriminative bag-of-words (DBoW) model that can both adapt to appearance variations over time and reduce the commonly observed drifting problem in online tracking. Specifically, a contextual region containing both the object and its surroundings is explored to construct a compact representation with two bags-of-words. Each visual word is learned to carry discriminative appearance cues for the object. In order to alleviate the drifting problem, an adaptive… CONTINUE READING

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