TY - GEN
T1 - An automatic method for computerized head and facial anthropometry
AU - Fang, Jing Jing
AU - Fang, Sheng Yi
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
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U2 - 10.1007/978-3-642-21799-9_2
DO - 10.1007/978-3-642-21799-9_2
M3 - Conference contribution
AN - SCOPUS:79960307894
SN - 9783642217982
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 12
EP - 21
BT - Digital Human Modeling - Third International Conference, ICDHM 2011, Held as Part of HCI International 2011, Proceedings
T2 - 3rd International Conference on Digital Human Modeling, ICDHM 2011, Held as Part of HCI International 2011
Y2 - 9 July 2011 through 14 July 2011
ER -