A quantitative evaluation for 3D face reconstruction algorithms

Vuong Le, Yuxiao Hu, Thomas S Huang

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

Abstract

In this work, we proposed to use quantitative method to evaluate the accuracy of 3D face reconstruction algorithms. The reconstructed 3D faces are first aligned to the ground truth by Iterative Closest Point (ICP) algorithm and then the shape difference between the two 3D faces is described by Signal to Noise Ratio (SNR). Finally, the error maps (EM) illustrated the reconstruction errors on corresponded vertices in different dimensions. Comparing with the subjective and indirect evaluation methods, the proposed method provides more precise and detailed evaluations for face shape reconstruction. Based on the SNR, different 3D face reconstruction algorithms can be compared directly and the EM also can suggest guidance for feature extraction.

Original languageEnglish (US)
Title of host publication2009 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings, ICASSP 2009
Pages1269-1272
Number of pages4
DOIs
StatePublished - Sep 23 2009
Event2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009 - Taipei, Taiwan, Province of China
Duration: Apr 19 2009Apr 24 2009

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009
CountryTaiwan, Province of China
CityTaipei
Period4/19/094/24/09

Keywords

  • 3D face reconstruction
  • Error map
  • Iterative closest points
  • Quantitative evaluation

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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