Patterns of Eye Movements When Observers Judge Female Facial Attractiveness

Perception of Nasal Aesthetics: Nose or Face?

BACKGROUND

Aesthetic assessment of the nose might not be limited to the nose as an isolated facial unit but might be the result of a broader perception of the whole facial image. The aim of this study was to investigate if the aesthetic evaluation of a nose is made by sole observation of the nose or influenced by the other features of the face.

METHODS

Nose and face photographs of 20 voluntary models were taken from five different angles and merged into a single image of just the noses and whole faces of each model. First the nose and then the face photos were sent to a reviewer group consisting of 100 individuals from different professions to evaluate the nose's beauty on standard questionnaires with a four-week interval to complicate the recall process.

RESULTS

Aesthetic evaluation of the isolated nose (Group 1) and the nose with the whole face (Group 2) were compared through Visual Analog Scale (VAS) scores ranging from 1 to 10 (1: the least, 10: the highest). The mean VAS score of the Whole Face Group (5.26 ± 1.28) was significantly higher than the score of the Isolated Nose Group (4.50 ± 1.32) (p 0.001). There was no significant difference between the scores of reviewers considering their gender, profession, or experience of having an aesthetic operation previously.

CONCLUSION

Current study revealed that in the evaluation of the beauty of the nose, the holistic perception of the face is as important as the perfection of the angles and proportions within the nose itself.

LEVEL OF EVIDENCE V

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A novel facial attractiveness evaluation system based on face shape, facial structure features and skin

Facial attractiveness is an important research direction of genetic psychology and cognitive psychology, and its results are significant for the study of face evolution and human evolution. However, previous studies have not put forward a comprehensive evaluation system of facial attractiveness. Traditionally, the establishment of facial attractiveness evaluation system was based on facial geometric features, without facial skin features. In this paper, combined with big data analysis, evaluation of face in real society and literature research, we found that skin also have a significant impact on facial attractiveness, because skin could reflect age, wrinkles and healthful qualities, thus affected the human perception of facial attractiveness. Therefore, we propose a comprehensive and novel facial attractiveness evaluation system based on face shape structural features, facial structure features and skin texture feature. In order to apply face shape structural features to the evaluation of facial attractiveness, the classification of face shape is the first step. Face image dataset is divided according to face shape, and then facial structure features and skin texture features that represent facial attractiveness are extracted and fused. The machine learning algorithm with the best prediction performance is selected in the face shape structural subsets to predict facial attractiveness. Experimental results show that the facial attractiveness evaluation performance can be improved by the method based on classification of face shape and multi-features fusion, the facial attractiveness scores obtained by the proposed system correlates better with human ratings. Our evaluation system can help people project their cognition of facial attractiveness into artificial agents they interact with.

Data-Driven Research on the Matching Degree of Eyes, Eyebrows and Face Shapes

There is a close relationship between the attractiveness of the face and the facial features. The shape of the facial features determines the level of attractiveness, in which the eyes and eyebrows are particularly vital. In this article, we proposed a method to study the facial attractiveness by combining global face shape and local geometric features of eye and eyebrow and using computer big data analysis for assistance. Firstly, we collected 300 images of East Asian female and use machine learning methods to evaluate the attractiveness scores of face images. Secondly, geometric models were constructed separately for the eyebrows and the eyes to obtain their geometric and shape features. Correlation analysis was performed on the obtained data to study their shape matching of different facial attractiveness rating levels. Finally, the relationship between the shape of face and eyebrows was analyzed by combining the facial ratio and the geometric features of the eyebrows. The research in this article can provide reference for medical and beauty institutions and women’s makeup, and further study in the field of facial aesthetic analysis based on geometric features.