文件名称:Kapoor_Winn

  • 所属分类:
  • 图形图像处理(光照,映射..)
  • 资源属性:
  • [PDF]
  • 上传时间:
  • 2012-11-26
  • 文件大小:
  • 290kb
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  • 提 供 者:
  • Da***
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This paper introduces the Located Hidden Random Field

(LHRF), a conditional model for simultaneous part-based detection and

segmentation of objects of a given class. Given a training set of images

with segmentation masks for the object of interest, the LHRF automati-

cally learns a set of parts that are both discriminative in terms of appear-

ance and informative about the location of the object. By introducing

the global position of the object as a latent variable, the LHRF models

the long-range spatial con guration of these parts, as well as their local

interactions. Experiments on benchmark datasets show that the use of

discriminative parts leads to state-of-the-art detection and segmentation

performance, with the additional bene t of obtaining a labeling of the

object s component parts.
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Kapoor_Winn.pdf

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