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Boosting relative spaces for categorizing objects with large intra-class variation

Published: 26 October 2008 Publication History

Abstract

In this paper, a novel method for object categorization is proposed. We first analyze the phenomenon of large intra-class variation and attribute it to the "subcategory" problem. To reveal the local and distinct properties of the different subcategories, relative spaces are constructed. Then the weighted FLDs (Fisher Linear Discriminant) as weak learners trained in relative spaces are integrated with the boosting framework to form the final classifier. Experiments on 8 categories from Caltech database show the effectiveness of our algorithm.

References

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H. Zhang, A. Berg, M. Maire, and J. Malik, Svm-knn: Discriminative nearest neighbor classification for visual category recognition, in CVPR, 2006.
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M. Schultz and T. Joachims, Learning a distance metric from relative comparisons, in NIPS, 2003.
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A. Frome, Y. Singer, and J. Malik, Image retrieval and classification using local distance functions, in NIPS, 2006.
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Andrea Frome, Learning Distance Functions for Exemplar-Based Object Recognition, Ph.D. thesis, August 2007.
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A. Frome, Y. Singer, F. Sha, and J. Malik, Learning Globally-Consistent Local Distance Functions for Shape-Based Image Retrieval and Classification, in ICCV 2007.
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A. Berg and J. Malik, Geometric blur for template matching, in CVPR, pp. 607--614, 2001.
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Cited By

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  • (2011)Gated classifiersProceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition10.1109/CVPR.2011.5995408(2673-2680)Online publication date: 20-Jun-2011
  • (2009)Random patch based video tracking via boosting the relative spacesProceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing10.1109/ICASSP.2009.4959809(1217-1220)Online publication date: 19-Apr-2009

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  1. Boosting relative spaces for categorizing objects with large intra-class variation

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    cover image ACM Conferences
    MM '08: Proceedings of the 16th ACM international conference on Multimedia
    October 2008
    1206 pages
    ISBN:9781605583037
    DOI:10.1145/1459359
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 26 October 2008

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    Author Tags

    1. adaboost
    2. geometric blur
    3. object categorization
    4. relative space

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    • Short-paper

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    MM08
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    MM08: ACM Multimedia Conference 2008
    October 26 - 31, 2008
    British Columbia, Vancouver, Canada

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    Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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    Cited By

    View all
    • (2011)Gated classifiersProceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition10.1109/CVPR.2011.5995408(2673-2680)Online publication date: 20-Jun-2011
    • (2009)Random patch based video tracking via boosting the relative spacesProceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing10.1109/ICASSP.2009.4959809(1217-1220)Online publication date: 19-Apr-2009

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