3D face recognition under pose varying environments

Hwanjong Song, Ukil Yang, Kwanghoon Sohn

Research output: Chapter in Book/Report/Conference proceedingChapter

7 Citations (Scopus)

Abstract

This paper describes a novel three-dimensional (3D) face recognition method when the head pose varies severely. Given an unknown 3D face, we extract several invariant facial features based on the facial geometry. We perform a Error Compensated Singular Value Decomposition (EC-SVD) for 3D face recognition. The novelty of the proposed EC-SVD procedure lies in compensating for the error for each rotation axis accurately. When the pose of a face is estimated, we propose a novel two-stage 3D face recognition algorithm. We first select face candidates based on the 3D-based nearest neighbor classifier and then the depth-based template matching is performed for final recognition. From the experimental results, less than a 0.2 degree error in average has been achieved for the 3D head pose estimation and all faces are correctly matched based on our proposed method.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsKijoon Chae, Moti Yung
PublisherSpringer Verlag
Pages333-347
Number of pages15
ISBN (Print)3540208275
DOIs
Publication statusPublished - 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2908
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Song, H., Yang, U., & Sohn, K. (2004). 3D face recognition under pose varying environments. In K. Chae, & M. Yung (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 333-347). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2908). Springer Verlag. https://doi.org/10.1007/978-3-540-24591-9_25