Accounting for private taste: Facial shape analysis of attractiveness and inter-individual variance

Takumi Tanaka, Jan Mikuni, Daisuke Shimane, Koyo Nakamura, Katsumi Watanabe

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

1 Citation (Scopus)

Abstract

Attractiveness is an important facial attribute, which could largely influence individuals' impressions or social relationship. Lately, numerous studies have examined the morphological facial features driving attractiveness. Notably, most of the studies have postulated the 'ground-truth', universal standards of facial attractiveness. However, in fact, it is well-reported that there are inter-individual differences in attractiveness judgments. These individual differences may be derived from individual preferences for certain morphological features in the faces. Nevertheless, there has been no direct empirical study to investigate the variances in the evaluation of facial attractiveness. In this study, we examined the quantitative relationships between morphological facial features and the judgments of attractiveness ratings for the faces. We found that the variances in attractiveness ratings could be partly predicted by some traditional machine learning, and that the sharpness of face outlines and morphological features representing the smile expression could have impacts on the amounts of the variances.

Original languageEnglish
Title of host publicationKST 2020 - 2020 12th International Conference on Knowledge and Smart Technology
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages203-206
Number of pages4
ISBN (Electronic)9781728144665
DOIs
Publication statusPublished - 2020 Jan
Event12th International Conference on Knowledge and Smart Technology, KST 2020 - Pattaya, Chonburi, Thailand
Duration: 2020 Jan 292020 Feb 1

Publication series

NameKST 2020 - 2020 12th International Conference on Knowledge and Smart Technology

Conference

Conference12th International Conference on Knowledge and Smart Technology, KST 2020
CountryThailand
CityPattaya, Chonburi
Period20/1/2920/2/1

Keywords

  • Facial Attractiveness
  • Individual difference
  • Private taste
  • Sexual dimorphism

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Decision Sciences (miscellaneous)
  • Information Systems and Management

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