Assessing facial beauty through proportion analysis by image processing and supervised learning

Gunes, H; Piccardi, M

Assessing facial beauty through proportion analysis by image processing and supervised learning

Gunes, H Piccardi, M

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Publication Type:: Journal Article
Citation:: International Journal of Human Computer Studies, 2006, 64 (12), pp. 1184 - 1199
Issue Date:: 2006-12-01

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Field	Value	Language
dc.contributor.author	Gunes, H	en_US
dc.contributor.author	Piccardi, M https://orcid.org/0000-0001-9250-6604	en_US
dc.date.issued	2006-12-01	en_US
dc.identifier.citation	International Journal of Human Computer Studies, 2006, 64 (12), pp. 1184 - 1199	en_US
dc.identifier.issn	1071-5819	en_US
dc.identifier.uri	http://hdl.handle.net/10453/4141
dc.description.abstract	Perception of universal facial beauty has long been debated amongst psychologists and anthropologists. In this paper, we perform experiments to evaluate the extent of universal beauty by surveying a number of diverse human referees to grade a collection of female facial images. Results obtained show that there exists a strong central tendency in the human grades, thus exhibiting agreement on beauty assessment. We then trained an automated classifier using the average human grades as the ground truth and used it to classify an independent test set of facial images. The high accuracy achieved proves that this classifier can be used as a general, automated tool for objective classification of female facial beauty. Potential applications exist in the entertainment industry, cosmetic industry, virtual media, and plastic surgery. © 2006 Elsevier Ltd. All rights reserved.	en_US
dc.relation.ispartof	International Journal of Human Computer Studies	en_US
dc.relation.isbasedon	10.1016/j.ijhcs.2006.07.004	en_US
dc.subject.classification	Human Factors	en_US
dc.title	Assessing facial beauty through proportion analysis by image processing and supervised learning	en_US
dc.type	Journal Article
utslib.citation.volume	12	en_US
utslib.citation.volume	64	en_US
utslib.for	080602 Computer-Human Interaction	en_US
utslib.for	0806 Information Systems	en_US
utslib.for	1702 Cognitive Sciences	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
utslib.copyright.status	open_access
pubs.issue	12	en_US
pubs.publication-status	Published	en_US
pubs.volume	64	en_US

Abstract:

Perception of universal facial beauty has long been debated amongst psychologists and anthropologists. In this paper, we perform experiments to evaluate the extent of universal beauty by surveying a number of diverse human referees to grade a collection of female facial images. Results obtained show that there exists a strong central tendency in the human grades, thus exhibiting agreement on beauty assessment. We then trained an automated classifier using the average human grades as the ground truth and used it to classify an independent test set of facial images. The high accuracy achieved proves that this classifier can be used as a general, automated tool for objective classification of female facial beauty. Potential applications exist in the entertainment industry, cosmetic industry, virtual media, and plastic surgery. © 2006 Elsevier Ltd. All rights reserved.

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http://hdl.handle.net/10453/4141