A novel face representation toward pose invariant face recognition

Liang Yu, Sei Ichiro Kamata, Yong Fang

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

Abstract

Though elastic bunch graph matching (EBGM) has a good performance on face recognition in the distortion of facial expression, it is still not robust enough to in-depth rotation. To solve this problem, a novel face representation approach based on the space-filling tree is proposed in this paper. This kind of representation shows a better performance than Elastic bunch graph matching (EBGM) in in-depth rotation of pose especially when there are only frontal images in the training set. With the proposed face representation approach, the face recognition system is built. Experimental results on the FERET standard database show that the proposed face representation approach is more effective and robust to the in-depth rotation of pose when there are only frontal images in the training set.

Original languageEnglish
Title of host publicationTENCON 2010 - 2010 IEEE Region 10 Conference
Pages179-183
Number of pages5
DOIs
Publication statusPublished - 2010 Dec 1
Event2010 IEEE Region 10 Conference, TENCON 2010 - Fukuoka, Japan
Duration: 2010 Nov 212010 Nov 24

Publication series

NameIEEE Region 10 Annual International Conference, Proceedings/TENCON

Other

Other2010 IEEE Region 10 Conference, TENCON 2010
CountryJapan
CityFukuoka
Period10/11/2110/11/24

Keywords

  • Elastic bunch graph matching
  • Face recognition
  • Pose invariant
  • Space-filling tree

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering

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