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On the role of dimensionality in face authentication
Swiss Federal Institute of Technology, Lausanne.
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).ORCID iD: 0000-0002-4929-1262
Swiss Federal Institute of Technology, Lausanne.
2000 (English)In: Proceedings / [ed] Josef Bigün, Kerstin Malmqvist, Halmstad: Högskolan i Halmstad , 2000, p. 87-91Conference paper, Published paper (Other academic)
Abstract [en]

A study of the dimensionality of the Face Authentication problem using Principal Component Analysis (PCA) and a novel dimensionality reduction algorithm that we call Support Vector Features (SVF) is presented. Starting from a Gabor feature space, we show that PCA and SVF identify distinct subspaces with comparable authentication and generalisation performance. Experiments using KNN classifiers and Support Vector Machines (SVMs) indicate that the number of PCs or SVF required for the authentication performance to saturate heavily depends on the choice of the classifier. SVMs appear to be vulnerable to excessive PCA-based compression.

Place, publisher, year, edition, pages
Halmstad: Högskolan i Halmstad , 2000. p. 87-91
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:hh:diva-14904OAI: oai:DiVA.org:hh-14904DiVA: diva2:408419
Conference
Symposium on image analysis, Halmstad March 7-8, 2000
Available from: 2011-04-04 Created: 2011-04-04 Last updated: 2017-09-27Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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  • de-DE
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  • nn-NO
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  • Other locale
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Output format
  • html
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  • asciidoc
  • rtf