Ecole d'ingénieur et centre de recherche en Sciences du numérique

Perspective morphometric criteria for facial beauty and proportion assessment

Ulrich, Luca; Dugelay, Jean-Luc; Vezzetti, Enrico; Moos, Sandro; Marcolin, Federica

Applied Sciences, Vol.10, N°1, 18 December 2019

Common sense usually considers the assessment of female human attractiveness to be subjective. Nevertheless, in the past decades, several studies and experiments showed that an objective component in beauty assessment exists and can be strictly related, even if it does not match, with proportions of features. Proportions can be studied through analysis of the face, which relies on landmarks, i.e., specific points on the facial surface, which are shared by everyone, and measurements between them. In this work, several measures have been gathered from studies in the literature considering datasets of beautiful women to build a set of measures that can be defined as suggestive of female attractiveness. The resulting set consists of 29 measures applied to a public dataset, the Bosphorus database, whose faces have been both analyzed by the developed methodology based on the expanded set of measures and judged by human observers. Results show that the set of chosen measures is significant in terms of attractiveness evaluation, confirming the key role of proportions in beauty assessment; furthermore, the sorting of identified measures has been performed to identify the most significant canons involved in the evaluation

Document Doi Bibtex

Titre:Perspective morphometric criteria for facial beauty and proportion assessment
Mots Clés:face analysis; face proportions; attractiveness; 3D landmarks; features extraction
Département:Sécurité numérique
Eurecom ref:6146
Copyright: MDPI
Bibtex: @article{EURECOM+6146, doi = {}, year = {2019}, month = {12}, title = {{P}erspective morphometric criteria for facial beauty and proportion assessment}, author = {{U}lrich, {L}uca and {D}ugelay, {J}ean-{L}uc and {V}ezzetti, {E}nrico and {M}oos, {S}andro and {M}arcolin, {F}ederica}, journal = {{A}pplied {S}ciences, {V}ol.10, {N}°1, 18 {D}ecember 2019}, url = {} }
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