scholarly journals Data-driven enhancement of facial attractiveness

2008 ◽  
Vol 27 (3) ◽  
pp. 1-9 ◽  
Author(s):  
Tommer Leyvand ◽  
Daniel Cohen-Or ◽  
Gideon Dror ◽  
Dani Lischinski
Keyword(s):  
Facial Attractiveness ◽  
Data Driven

A landmark-based data-driven approach on 2.5D facial attractiveness computation

2017 ◽  
Vol 238 ◽  
pp. 168-178 ◽  
Author(s):  
Shu Liu ◽  
Yang-Yu Fan ◽  
Zhe Guo ◽  
Ashok Samal ◽  
Afan Ali
Keyword(s):  
Facial Attractiveness ◽  
Data Driven ◽  
Data Driven Approach

scholarly journals Data-driven enhancement of facial attractiveness

2008 ◽  
Author(s):  
Tommer Leyvand ◽  
Daniel Cohen-Or ◽  
Gideon Dror ◽  
Dani Lischinski
Keyword(s):  
Facial Attractiveness ◽  
Data Driven

scholarly journals A data-driven test for cross-cultural differences in face preferences

2018 ◽  
Author(s):  
Lingshan Zhang ◽  
Iris Jasmin Holzleitner ◽  
Anthony J Lee ◽  
Vanessa Fasolt ◽  
Hongyi Wang ◽  
...  
Keyword(s):  
Cultural Differences ◽  
Principal Components ◽  
Facial Attractiveness ◽  
Cross Cultural ◽  
Data Driven ◽  
Cross Cultural Differences ◽  
Data Driven Approach ◽  
The Uk ◽  
Data Driven Test

Previous research has shown strong cross-cultural agreement in facial attractiveness judgments. However, these studies all used a theory-driven approach in which responses to specific facial characteristics are compared between cultures. This approach is constrained by the predictions that can be derived from existing theories and can therefore bias impressions of the extent of cross-cultural agreement in face preferences. We directly addressed this problem by using a data-driven, rather than theory-driven, approach to compare facial attractiveness judgments made by Chinese-born participants who were resident in China, Chinese-born participants currently resident in the UK, and UK-born and -resident White participants. Analyses of the principal components along which faces naturally varied suggested that Chinese and White UK participants used face information in different ways, at least when judging women’s facial attractiveness. In other words, the data-driven approach used in the current study revealed some cross-cultural differences in face preferences that were not apparent in studies using theory-driven approaches.

scholarly journals Comparing theory-driven and data-driven attractiveness models using images of real women’s faces

2018 ◽  
Author(s):  
Iris Jasmin Holzleitner ◽  
Anthony J Lee ◽  
Amanda Hahn ◽  
Michal Kandrik ◽  
Jeanne Bovet ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Social Interaction ◽  
Sexual Dimorphism ◽  
Young Adult ◽  
Adult Female ◽  
Critical Role ◽  
Facial Attractiveness ◽  
Data Driven ◽  
Neutral Model ◽  
Face Images

Facial attractiveness plays a critical role in social interaction, influencing many different social outcomes. However, the factors that influence facial attractiveness judgments remain relatively poorly understood. Here, we used a sample of 594 young adult female face images to compare the performance of existing theory-driven models of facial attractiveness and a data-driven (i.e., theory-neutral) model. Our data-driven model and a theory-driven model including various traits commonly studied in facial attractiveness research (asymmetry, averageness, sexual dimorphism, body mass index, and representational sparseness) performed similarly well. By contrast, univariate theory-driven models performed relatively poorly. These results (1) highlight the utility of data driven models of facial attractiveness and (2) suggest that theory-driven research on facial attractiveness would benefit from greater adoption of multivariate approaches, rather than the univariate approaches that they currently almost exclusively employ.

scholarly journals Data-Driven Facial Attractiveness of Chinese Male With Epoch Characteristics

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 10956-10966
Author(s):  
Jian Zhao ◽  
Meng Cao ◽  
Xie Xie ◽  
Miao Zhang ◽  
Lin Wang
Keyword(s):  
Facial Attractiveness ◽  
Data Driven ◽  
Chinese Male

scholarly journals A new data-driven mathematical model dissociates attractiveness from sexual dimorphism of human faces

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Koyo Nakamura ◽  
Katsumi Watanabe
Keyword(s):  
Sexual Dimorphism ◽  
Facial Attractiveness ◽  
Influential Factor ◽  
Data Driven ◽  
Male And Female ◽  
True Preference ◽  
Facial Stimuli ◽  
Positive Correlations ◽  
Human Faces ◽  
Perceived Attractiveness

Abstract Human facial attractiveness is evaluated by using multiple cues. Among others, sexual dimorphism (i.e. masculinity for male faces/femininity for female faces) is an influential factor of perceived attractiveness. Since facial attractiveness is judged by incorporating sexually dimorphic traits as well as other cues, it is theoretically possible to dissociate sexual dimorphism from facial attractiveness. This study tested this by using a data-driven mathematical modelling approach. We first analysed the correlation between perceived masculinity/femininity and attractiveness ratings for 400 computer-generated male and female faces (Experiment 1) and found positive correlations between perceived femininity and attractiveness for both male and female faces. Using these results, we manipulated a set of faces along the attractiveness dimension while controlling for sexual dimorphism by orthogonalisation with data-driven mathematical models (Experiment 2). Our results revealed that perceived attractiveness and sexual dimorphism are dissociable, suggesting that there are as yet unidentified facial cues other than sexual dimorphism that contribute to facial attractiveness. Future studies can investigate the true preference of sexual dimorphism or the genuine effects of attractiveness by using well-controlled facial stimuli like those that this study generated. The findings will be of benefit to the further understanding of what makes a face attractive.

scholarly journals A Data-Driven Test for Cross-Cultural Differences in Face Preferences

Perception ◽  
2019 ◽  
Vol 48 (6) ◽  
pp. 487-499 ◽  
Author(s):  
Lingshan Zhang ◽  
Iris J. Holzleitner ◽  
Anthony J. Lee ◽  
Hongyi Wang ◽  
Chengyang Han ◽  
...  
Keyword(s):  
Cultural Differences ◽  
Principal Components ◽  
Facial Attractiveness ◽  
Cross Cultural ◽  
Data Driven ◽  
Cross Cultural Differences ◽  
Data Driven Approach ◽  
The Uk ◽  
Data Driven Test

Previous research has shown strong cross-cultural agreement in facial attractiveness judgments. However, these studies all used a theory-driven approach in which responses to specific facial characteristics are compared between cultures. This approach is constrained by the predictions that can be derived from existing theories and can therefore bias impressions of the extent of cross-cultural agreement in face preferences. We directly addressed this problem by using a data-driven, rather than theory-driven, approach to compare facial attractiveness judgments made by Chinese-born participants who were resident in China, Chinese-born participants currently resident in the UK, and UK-born and UK-resident White participants. Analyses of the principal components along which faces naturally varied suggested that Chinese and White UK participants used face information in different ways, at least when judging women’s facial attractiveness. In other words, the data-driven approach used in this study revealed some cross-cultural differences in face preferences that were not apparent in studies using theory-driven approaches.

scholarly journals Data-driven mathematical model of East-Asian facial attractiveness: the relative contributions of shape and reflectance to attractiveness judgements

2019 ◽  
Vol 6 (5) ◽  
pp. 182189 ◽  
Author(s):  
Koyo Nakamura ◽  
Katsumi Watanabe
Keyword(s):  
East Asian ◽  
Facial Attractiveness ◽  
Data Driven ◽  
Multiple Cues ◽  
Visual Processes ◽  
Facial Shape ◽  
General Preference ◽  
Face Stimuli ◽  
Prior Hypothesis ◽  
Asian Face

Facial attractiveness is judged through a combination of multiple cues including morphology (facial shape) and skin properties (facial reflectance). While several studies have examined the way in which people in Western cultures judge facial attractiveness, there have been fewer investigations into non-Western attitudes. This is because stimuli that quantitatively vary the attractiveness of non-Western faces are rare. In the present study, we built a model of the attractiveness of East-Asian faces, judged by East-Asian observers. Therefore, 400 computer-generated East-Asian faces were created and attractiveness rating scores were collected from Japanese observers. Data-driven mathematical calculations were used to identify quantitative links between facial attractiveness and shape and reflectance properties, with no prior hypothesis. Results indicate that faces with larger eyes, smaller noses and brighter skin are judged as more attractive, regardless of the sex of the faces, possibly reflecting a general preference for femininity. Shape is shown to be a strong determinant of attractiveness for both male and female faces, while reflectance properties are less important in judging male facial attractiveness. Our model provides a tool to effectively produce East-Asian face stimuli that quantitatively varies attractiveness and can be used to elucidate visual processes related to attractiveness judgements.

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