Facial component extraction and face recognition with support vector machines

Dihua Xi, Igor T. Podolak, Seong Whan Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

44 Citations (Scopus)

Abstract

A method for face recognition is proposed which uses a two-step approach: first, a number of facial components are found, which are then glued together, and the resulting face vector is recognized as representing one of the possible persons. During the extraction step, a wavelet statistics subsystem provides the possible locations of the eyes and mouth, which are used by a support vector machine (SVM) subsystem to extract the facial components. The use of a wavelet statistics subsystem speeds up the recognition process markedly. Both the feature detection SVMs and the wavelet statistics subsystem are trained on a small number of actual images with marked features. Afterwards, a large number of face vectors are constructed, which are then classified with another set of SVM machines.

Original languageEnglish
Title of host publicationProceedings - 5th IEEE International Conference on Automatic Face Gesture Recognition, FGR 2002
PublisherIEEE Computer Society
Pages83-88
Number of pages6
ISBN (Print)0769516025, 9780769516028
DOIs
Publication statusPublished - 2002
Event5th IEEE International Conference on Automatic Face Gesture Recognition, FGR 2002 - Washington, DC, United States
Duration: 2002 May 202002 May 21

Publication series

NameProceedings - 5th IEEE International Conference on Automatic Face Gesture Recognition, FGR 2002

Other

Other5th IEEE International Conference on Automatic Face Gesture Recognition, FGR 2002
Country/TerritoryUnited States
CityWashington, DC
Period02/5/2002/5/21

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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