This paper introduces a texture representation suitable for recognizing images of textured surfaces under a wide range of transformations, including viewpoint changes and nonrigid deformations. At the feature extraction stage, a sparse set of affine-invariant local patches is extracted from the image. This spatial selection process permits the computation of characteristic scale and neighborhood shape for every texture element. The proposed texture representation is evaluated in retrieval and classification tasks using the entire Brodatz database and a collection of photographs of textured surfaces taken from different viewpoints.


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    Title :

    A sparse texture representation using affine-invariant regions


    Contributors:
    Lazebnik, S. (author) / Schmid, C. (author) / Ponce, J. (author)


    Publication date :

    2003-01-01


    Size :

    2018297 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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