Automatic pose-normalized 3D face modeling and recognition systems

Sunjin Yu, Kwontaeg Choi, Sangyoun Lee

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

1 Citation (Scopus)

Abstract

Pose-variation factors present a big problem in 2D face recognition. To solve this problem, we designed a 3D face acquisition system which was able to generate multi-view images. However, this created another pose-estimation problem in terms of normalizing the 3D face data. This paper presents an automatic pose-normalized 3D face data acquisition method that is able to perform both 3D face modeling and 3D face pose-normalization at once. The proposed method uses 2D information with the AAM (Active Appearance Model) and 3D information with a 3D normal vector. The proposed system is based on stereo vision and a structured light system which consists of 2 cameras and 1 projector. In orsder to verify the performance of the proposed method, we designed an experiment for 2.5D face recognition. Experimental results showed that the proposed method is robust against pose variation.

Original languageEnglish
Title of host publicationAdvances in Image and Video Technology - First Pacific Rim Symposium, PSIVT 2006, Proceedings
Pages652-661
Number of pages10
DOIs
Publication statusPublished - 2006 Dec 1
Event1st Pacific Rim Symposium on Image and Video Technology, PSIVT 2006 - Hsinchu, Taiwan, Province of China
Duration: 2006 Dec 102006 Dec 13

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4319 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other1st Pacific Rim Symposium on Image and Video Technology, PSIVT 2006
CountryTaiwan, Province of China
CityHsinchu
Period06/12/1006/12/13

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Yu, S., Choi, K., & Lee, S. (2006). Automatic pose-normalized 3D face modeling and recognition systems. In Advances in Image and Video Technology - First Pacific Rim Symposium, PSIVT 2006, Proceedings (pp. 652-661). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4319 LNCS). https://doi.org/10.1007/11949534-65