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Pictorial Portrait Indexing Using View-Based Eigen-Eyes

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Visual Information and Information Systems (VISUAL 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1614))

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Abstract

A hierarchical database indexing method for a pictorial portrait database is presented, which is based on Principal Component Analysis (PCA). The description incorporates the eyes, as the most salient region in the portraits. The algorithm has been tested on 600 portrait miniatures of the Austrian National Library.

This work was supported by the Austrian Science Foundation (FWF) under grants P12028-MAT and S7000-MAT.

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Author information

Authors and Affiliations

  1. PRIP-Vienna University of Technology, Treitlstr. 3, 183/2, A-1040, Vienna, Austria

    C. Saraceno, M. Reiter, P. Kammerer, E. Zolda & W. Kropatsch

Authors
  1. C. Saraceno
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  2. M. Reiter
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  3. P. Kammerer
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  4. E. Zolda
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  5. W. Kropatsch
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Editor information

Editors and Affiliations

  1. Computer Science Department, Leiden University, Niels Bohrweg 1, 2333 CA, Leiden, The Netherlands

    Dionysius P. Huijsmans

  2. Research Institute Computer Science, University of Amsterdam, Kruislaan 403, 1098 SJ, Amsterdam, The Netherlands

    Arnold W. M. Smeulders

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© 1999 Springer-Verlag Berlin Heidelberg

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Saraceno, C., Reiter, M., Kammerer, P., Zolda, E., Kropatsch, W. (1999). Pictorial Portrait Indexing Using View-Based Eigen-Eyes. In: Huijsmans, D.P., Smeulders, A.W.M. (eds) Visual Information and Information Systems. VISUAL 1999. Lecture Notes in Computer Science, vol 1614. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48762-X_80

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  • DOI: https://doi.org/10.1007/3-540-48762-X_80

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66079-8

  • Online ISBN: 978-3-540-48762-3

  • eBook Packages: Springer Book Archive

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