Structural Correlation Filter for Robust Visual Tracking

@article{Liu2016StructuralCF,
  title={Structural Correlation Filter for Robust Visual Tracking},
  author={Si Liu and Tianzhu Zhang and Xiaochun Cao and Changsheng Xu},
  journal={2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2016},
  pages={4312-4320}
}
In this paper, we propose a novel structural correlation filter (SCF) model for robust visual tracking. The proposed SCF model takes part-based tracking strategies into account in a correlation filter tracker, and exploits circular shifts of all parts for their motion modeling to preserve target object structure. Compared with existing correlation filter trackers, our proposed tracker has several advantages: (1) Due to the part strategy, the learned structural correlation filters are less… CONTINUE READING
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