3D face recognition based on fast feature detection and non-rigid iterative closest point

Can Tong, Seiichiro Kamata, Alireza Ahrary

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

Abstract

This paper presents a 3D face recognition algorithm using fast landmark detection and non-rigid iterative Closest Point (ICP) algorithm. The proposed approach can estimate the facial feature region using the anthropometric face model after pose correction, and accurately detect 9 facial landmarks (nose tip, sellion, inner and outer eye corners, nostrils and mouth center). An extension of ICP algorithm has also been proposed to matching the non-rigid 3D face shapes. Experimental results demonstrate that compared to the existing methods, the proposed approach can efficiently detect human facial landmarks and satisfactorily deal with the 3D face matching problem.

Original languageEnglish
Title of host publicationProceedings - 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009
Pages509-512
Number of pages4
Volume4
DOIs
Publication statusPublished - 2009
Event2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009 - Shanghai
Duration: 2009 Nov 202009 Nov 22

Other

Other2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009
CityShanghai
Period09/11/2009/11/22

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Keywords

  • 3D face recognition
  • Anthropometric face model
  • ICP
  • Landmark detection
  • Non-rigid

ASJC Scopus subject areas

  • Computer Science(all)
  • Control and Systems Engineering

Cite this

Tong, C., Kamata, S., & Ahrary, A. (2009). 3D face recognition based on fast feature detection and non-rigid iterative closest point. In Proceedings - 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009 (Vol. 4, pp. 509-512). [5357633] https://doi.org/10.1109/ICICISYS.2009.5357633