Corpus ID: 2974172

Visual Tracking via Learning Dynamic Patch-based Graph Representation

@article{Li2017VisualTV,
  title={Visual Tracking via Learning Dynamic Patch-based Graph Representation},
  author={Chenglong Li and L. Lin and W. Zuo and Jin Tang and Ming-Hsuan Yang},
  journal={ArXiv},
  year={2017},
  volume={abs/1710.01444}
}
  • Chenglong Li, L. Lin, +2 authors Ming-Hsuan Yang
  • Published 2017
  • Computer Science
  • ArXiv
  • Existing visual tracking methods usually localize a target object with a bounding box, in which the performance of the foreground object trackers or detectors is often affected by the inclusion of background clutter. To handle this problem, we learn a patch-based graph representation for visual tracking. The tracked object is modeled by with a graph by taking a set of non-overlapping image patches as nodes, in which the weight of each node indicates how likely it belongs to the foreground and… CONTINUE READING
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