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  • Structured Learning Approach to Image Descriptor Combination

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    85887_1.pdf (489.0Kb)
    Author(s)
    Zhou, J
    Fu, Z
    Robles-Kelly, A
    Griffith University Author(s)
    Zhou, Jun
    Year published
    2011
    Metadata
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    Abstract
    In this study, the authors address the problem of combining descriptors for purposes of object categorisation and classification. The authors cast the problem in a structured learning setting by viewing the classifier bank and the codewords used in the categorisation and classification tasks as random fields. In this manner, the authors can abstract the problem into a graphical model setting, in which the fusion operation is a transformation over the field of descriptors and classifiers. Thus, the problem reduces itself to that of recovering the optimal transformation using a cost function which is convex and can be converted ...
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    In this study, the authors address the problem of combining descriptors for purposes of object categorisation and classification. The authors cast the problem in a structured learning setting by viewing the classifier bank and the codewords used in the categorisation and classification tasks as random fields. In this manner, the authors can abstract the problem into a graphical model setting, in which the fusion operation is a transformation over the field of descriptors and classifiers. Thus, the problem reduces itself to that of recovering the optimal transformation using a cost function which is convex and can be converted into either a quadratic or linear programme. This cost function is related to the target function used in discrete Markov random field approaches. The authors demonstrate the utility of our algorithm for purposes of image classification and learning class categories on two datasets.
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    Journal Title
    IET Computer Vision
    Volume
    5
    Issue
    2
    DOI
    https://doi.org/10.1049/iet-cvi.2010.0080
    Copyright Statement
    © 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subject
    Computer vision
    Cognitive and computational psychology
    Publication URI
    http://hdl.handle.net/10072/52095
    Collection
    • Journal articles

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