Automatic head and facial feature extraction based on geometry variations

Sheng Yi Fang, Jing Jing Fang

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

Facial anthropometry plays an important role in ergonomic applications. Most ergonomically designed products depend on stable and accurate human body measurement data. Our research automatically identifies human facial features based on three-dimensional geometric relationships, revealing a total of 67 feature points and 24 feature lines more than the definitions associated with MPEG-4. In this study, we also verify the replicability, robustness, and accuracy of this feature set. Even with a lower-density point cloud from a non-dedicated head scanner, this method can provide robust results, with 86.6% validity in the 5 mm range. We also analyze the main 31 feature points on the human face, with 96.7% validity of less than 5 mm.

Original languageEnglish
Pages (from-to)1729-1739
Number of pages11
JournalCAD Computer Aided Design
Volume43
Issue number12
DOIs
Publication statusPublished - 2011 Dec

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design
  • Industrial and Manufacturing Engineering

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