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From local similarity to global coding: An application to image classification
, Article Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Portland, OR ; 2013 , Pages 2794-2801 ; 10636919 (ISSN) ; Rabiee, H. R ; Farajtabar, M ; Ghazvininejad, M ; Sharif University of Technology
2013
Abstract
Bag of words models for feature extraction have demonstrated top-notch performance in image classification. These representations are usually accompanied by a coding method. Recently, methods that code a descriptor giving regard to its nearby bases have proved efficacious. These methods take into account the nonlinear structure of descriptors, since local similarities are a good approximation of global similarities. However, they confine their usage of the global similarities to nearby bases. In this paper, we propose a coding scheme that brings into focus the manifold structure of descriptors, and devise a method to compute the global similarities of descriptors to the bases. Given a local...