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A. Holub and P. Perona, “A Discriminative Framework for Modelling Object Classes,” IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Diego, 20-26 June 2005, pp. 664-671.

has been cited by the following article:

• TITLE: Multi-Scale Object Perception with Embedding Textural Space

  AUTHORS: Kewei Wu, Zhao Xie, Jun Gao

  KEYWORDS: Object Perception; Scale Space; Textural Manifold; Quad-Tree Structure; Nonparametric Estimation

  JOURNAL NAME: International Journal of Intelligence Science, Vol.2 No.2, April 24, 2012

  ABSTRACT: This paper mainly focuses on the issues about generic multi-scale object perception for detection or recognition. A novel computational model in visually-feature space is presented for scene & object representation to purse the underlying textural manifold statistically in nonparametric manner. The associative method approximately makes perceptual hierarchy in human-vision biologically coherency in specific quad-tree-pyramid structure, and the appropriate scale-value of different objects can automatically be selected by evaluating from well-defined scale function without any priori knowledge. The sufficient experiments truly demonstrate the effectiveness of scale determination in textural manifold with object localization rapidly.