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Face authentication with Gabor information on deformable graphs
Motorola, Inc., Geneva, Switzerland.
FASTCOM Technology, S.A., Lausanne.
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
1999 (English)In: IEEE Transactions on Image Processing, ISSN 1057-7149, E-ISSN 1941-0042, Vol. 8, no 4, 504-516 p.Article in journal (Refereed) Published
Abstract [en]

Elastic graph matching has been proposed as a practical implementation of dynamic link matching, which is a neural network with dynamically evolving links between a reference model and an input image. Each node of the graph contains features that characterize the neighborhood of its location in the image. The elastic graph matching usually consists of two consecutive steps, namely a matching with a rigid grid, followed by a deformation of the grid, which is actually the elastic part. The deformation step is introduced in order to allow for some deformation, rotation, and scaling of the object to be matched. This method is applied here to the authentication of human faces where candidates claim an identity that is to be checked. The matching error as originally suggested is not powerful enough to provide satisfying results in this case. We introduce an automatic weighting of the nodes according to their significance. We also explore the significance of the elastic deformation for an application of face-based person authentication. We compare performance results obtained with and without the second matching step. Results show that the deformation step slightly increases the performance, but has lower influence than the weighting of the nodes. The best results are obtained with the combination of both aspects. The results provided by the proposed method compare favorably with two methods that require a prior geometric face normalization, namely the synergetic and eigenface approaches

Place, publisher, year, edition, pages
New York, NY: IEEE Press, 1999. Vol. 8, no 4, 504-516 p.
Keyword [en]
face recognition, person authentication, face verification, local discriminants, computer vision, matching, Gabor filter, local orientation
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:hh:diva-14896DOI: 10.1109/83.753738ISI: 000079445700005Scopus ID: 2-s2.0-0032673243OAI: oai:DiVA.org:hh-14896DiVA: diva2:408425
Available from: 2011-04-04 Created: 2011-04-04 Last updated: 2017-06-20Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf