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T. Yuehua, M. Skubic, et al., “Performance Evaluation of SIFT-Based Descriptors for Object Recognition,” Pro- ceedings International Multi Conference of Engineering and Computer Scientists, Hong Kong, 17-19 March 2010, pp. 978-988.

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• 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.