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Multimedia Systems

, Volume 18, Issue 4, pp 283–293 | Cite as

CBIR with a subspace tree: principal component analysis versus averaging

  • Andreas WichertEmail author
  • André Filipe da  Silva Veríssimo
Regular Paper

Abstract

The subspace tree is an indexing method for large multi-media databases. The search in such a tree starts at the subspace with the lowest dimension. In this subspace, the set of all possible similar images is determined. In the next subspace, additional metric information corresponding to a higher dimension is used to reduce this set. We compare theoretically and empirically data-dependent mappings into subspaces (principal component analysis) with data-independent mapping (averaging). The empirical experiments are performed on an image collection of 30,000 images.

Keywords

CBIR High-dimensional indexing Image Pyramid PCA Subspace tree 

Notes

Acknowledgments

This work was supported by Fundao para a Cencia e Tecnologia (FCT) (INESC-ID multiannual funding) through the PIDDAC Program funds.

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Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Andreas Wichert
    • 1
    Email author
  • André Filipe da  Silva Veríssimo
    • 1
  1. 1.Department of InformaticsINESC-ID/IST, Technical University of LisboaLisbonPortugal

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