Ground from Figure Discrimination

نویسندگان

  • Arnon Amir
  • Michael Lindenbaum
چکیده

This paper proposes a new, e cient, gure from ground discrimination method. This algorithm is based on the assumption that background data features can be more easily detected than gure data features, thus emphasizing the background detection task (and implying the name of the method). Along the iterative labeling process, data features are sequentially and permanently labelled as "background", while more global information is being collected to assist with the coming decisions, until the process converges. This procedure creates a bootstrap mechanism which improves performance in very cluttered scenes. The method can be applied to many perceptual grouping cues, and an application to smoothness-based classi cation of edge points is given. A fast implementation using a kd-tree allows to work on large, realistic images. 2 List of symbols Gu Gm Eu Em Vdekk` nrmin uvvf vb v1; v2 E(r(vb)) du(v) dm(v) r(v) c(e) t(e) miss nepsilon fmissg fa nepsilon ffag 1; 2 nalpha 1,nalpha 2 nbeta ngamma npi nsigma

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تاریخ انتشار 1998