An automatic method for computerized head and facial anthropometry

Jing Jing Fang, Sheng Yi Fang

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

2 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. Head and facial anthropometric dimensions provide detailed information on head and facial surfaces to develop well-fitting, comfortable and functionally-effective facial masks, helmets or customized products. Accurate head and facial anthropometry also allows orthognathic surgeons and orthodontists to plan optimal treatments for patients. Our research uses an automatic, geometry-based facial feature extraction method to identify head and facial features, which can be used to develop a highly-accurate feature-based head model. In total, we have automatically located 17 digital length measurements and 5 digital tape measurements on the head and face. Compared to manual length-measurement, the average error, maximum error and standard deviations are 1.70mm, 5.63mm and 1.47mm, respectively, for intra-measurement, and 2.07mm, 5.63mm and 1.44mm, respectively, for inter-measurement. Compared to manual tape-measurement, the average maximum error and standard deviations are 1.52mm, 3.00mm and 0.96mm, respectively, for intra-measurement, and 2.74mm, 5.30mm and 1.79mm, respectively, for inter-measurement. Nearly all of length measurement data and tape measurement data meet the 5mm measuring error standard.

Original languageEnglish
Title of host publicationDigital Human Modeling - Third International Conference, ICDHM 2011, Held as Part of HCI International 2011, Proceedings
Pages12-21
Number of pages10
DOIs
Publication statusPublished - 2011
Event3rd International Conference on Digital Human Modeling, ICDHM 2011, Held as Part of HCI International 2011 - Orlando, FL, United States
Duration: 2011 Jul 92011 Jul 14

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6777 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other3rd International Conference on Digital Human Modeling, ICDHM 2011, Held as Part of HCI International 2011
Country/TerritoryUnited States
CityOrlando, FL
Period11-07-0911-07-14

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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