Fast globally optimal 2D human detection with loopy graph models

@article{Tian2010FastGO,
  title={Fast globally optimal 2D human detection with loopy graph models},
  author={Tai-Peng Tian and Stan Sclaroff},
  journal={2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition},
  year={2010},
  pages={81-88}
}
This paper presents an algorithm for recovering the globally optimal 2D human figure detection using a loopy graph model. This is computationally challenging because the time complexity scales exponentially in the size of the largest clique in the graph. The proposed algorithm uses Branch and Bound (BB) to search for the globally optimal solution. The algorithm converges rapidly in practice and this is due to a novel method for quickly computing tree based lower bounds. The key idea is to… CONTINUE READING
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A study of part - based object class detection using complete graphs

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