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B. Johnson and Z. Xie, “Unsupervised Image Segmentation Evaluation and Refinement Using a Multi-Scale Approach,” ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 66, No. 4, 2011, pp. 473-483. doi:10.1016/j.isprsjprs.2011.02.006

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.