Kernel Codebooks for Scene Categorization View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2008

AUTHORS

Jan C. van Gemert , Jan-Mark Geusebroek , Cor J. Veenman , Arnold W. M. Smeulders

ABSTRACT

This paper introduces a method for scene categorization by modeling ambiguity in the popular codebook approach. The codebook approach describes an image as a bag of discrete visual codewords, where the frequency distributions of these words are used for image categorization. There are two drawbacks to the traditional codebook model: codeword uncertainty and codeword plausibility. Both of these drawbacks stem from the hard assignment of visual features to a single codeword. We show that allowing a degree of ambiguity in assigning codewords improves categorization performance for three state-of-the-art datasets. More... »

PAGES

696-709

References to SciGraph publications

  • 2001-06. Representing and Recognizing the Visual Appearance of Materials using Three-dimensional Textons in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 2004-11. Distinctive Image Features from Scale-Invariant Keypoints in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 1986. Density Estimation for Statistics and Data Analysis in NONE
  • 2001-05. Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 2007-04. Semantic Modeling of Natural Scenes for Content-Based Image Retrieval in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 2006. Adapted Vocabularies for Generic Visual Categorization in COMPUTER VISION – ECCV 2006
  • 2006. Sampling Strategies for Bag-of-Features Image Classification in COMPUTER VISION – ECCV 2006
  • Book

    TITLE

    Computer Vision – ECCV 2008

    ISBN

    978-3-540-88689-1
    978-3-540-88690-7

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-540-88690-7_52

    DOI

    http://dx.doi.org/10.1007/978-3-540-88690-7_52

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1048787563


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