Hong, Yu-Jin Nam, Gi Pyo Choi, Heeseung Cho, Junghyun Kim, Ig-Jae 2024-01-20T00:01:55Z 2024-01-20T00:01:55Z 2021-09-03 2017-12 2073-8994 https://pubs.kist.re.kr/handle/201004/121989 In this paper, we present a novel framework for automatically assessing facial attractiveness that considers four ratio feature sets as objective elements of facial attractiveness. In our framework, these feature sets are combined with three regression-based predictors to estimate a facial beauty score. To enhance the system's performance to make it comparable with human scoring, we apply a score fusion technique. Experimental results show that the attractiveness score obtained by the proposed framework better correlates with human assessments than the scores from other predictors. The framework's modularity allows any features or predictors to be integrated into the facial attractiveness measure. Our proposed framework can be applied to many beauty-related fields, such as the plastic surgery, cosmetics, and entertainment industries. English MDPI BEAUTY SYMMETRY SHAPE FACE PSYCHOLOGY PERCEPTION AESTHETICS MODELS A Novel Framework for Assessing Facial Attractiveness Based on Facial Proportions Article 10.3390/sym9120294 1 SYMMETRY-BASEL, v.9, no.12 SYMMETRY-BASEL 9 12 scie scopus 000419227200006 2-s2.0-85040030383 Multidisciplinary Sciences Science & Technology - Other Topics Article BEAUTY SYMMETRY SHAPE FACE PSYCHOLOGY PERCEPTION AESTHETICS MODELS facial attractiveness facial beauty ratio feature score fusion