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Pictorial Portrait Indexing Using View-Based Eigen-Eyes

Pictorial Portrait Indexing Using View-Based Eigen-Eyes

Book SeriesLecture Notes in Computer Science
PublisherSpringer Berlin / Heidelberg
ISSN0302-9743 (Print) 1611-3349 (Online)
VolumeVolume 1614/1999
BookVisual Information and Information Systems
DOI10.1007/3-540-48762-X
Copyright1999
ISBN978-3-540-66079-8
DOI10.1007/3-540-48762-X_80
Page655
Subject CollectionComputer Science
SpringerLink DateFriday, January 01, 1999
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Pictorial Portrait Indexing Using View-Based Eigen-Eyes

C. Saraceno6 Contact Information, M. Reiter6 Contact Information, P. Kammerer6 Contact Information, E. Zolda6 Contact Information and W. Kropatsch6 Contact Information

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

Contact Information C. Saraceno
Email: saraceno@prip.tuwien.ac.at

Contact Information M. Reiter
Email: rei@prip.tuwien.ac.at

Contact Information P. Kammerer
Email: paul@prip.tuwien.ac.at

Contact Information E. Zolda
Email: zolda@prip.tuwien.ac.at

Contact Information W. Kropatsch
Email: krw@prip.tuwien.ac.at
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