Subjectivity and complexity of facial attractiveness

The origin and meaning of facial beauty represent a longstanding puzzle. Despite the profuse literature devoted to facial attractiveness, its very nature, its determinants and the nature of inter-person differences remain controversial issues. Here we tackle such questions proposing a novel experimental approach in which human subjects, instead of rating natural faces, are allowed to efficiently explore the face-space and 'sculpt' their favorite variation of a reference facial image. The results reveal that different subjects prefer distinguishable regions of the face-space, highlighting the essential subjectivity of the phenomenon.The different sculpted facial vectors exhibit strong correlations among pairs of facial distances, characterising the underlying universality and complexity of the cognitive processes, and the relative relevance and robustness of the different facial distances.Comment: 15 pages, 5 figures. Supplementary information: 26 pages, 13 figure

First impressions: A survey on vision-based apparent personality trait analysis

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Personality analysis has been widely studied in psychology, neuropsychology, and signal processing fields, among others. From the past few years, it also became an attractive research area in visual computing. From the computational point of view, by far speech and text have been the most considered cues of information for analyzing personality. However, recently there has been an increasing interest from the computer vision community in analyzing personality from visual data. Recent computer vision approaches are able to accurately analyze human faces, body postures and behaviors, and use these information to infer apparent personality traits. Because of the overwhelming research interest in this topic, and of the potential impact that this sort of methods could have in society, we present in this paper an up-to-date review of existing vision-based approaches for apparent personality trait recognition. We describe seminal and cutting edge works on the subject, discussing and comparing their distinctive features and limitations. Future venues of research in the field are identified and discussed. Furthermore, aspects on the subjectivity in data labeling/evaluation, as well as current datasets and challenges organized to push the research on the field are reviewed.Peer ReviewedPostprint (author's final draft

An overview of selected orthodontic treatment need indices

Orthodontics is a fast developing science as well as the field of medicine in general. The attempt of this book is to propose new possibilities and new ways of thinking about Orthodontics beside the ones presented in established and outstanding publications available elsewhere. Some of the presented chapters transmit basic information, other clinical experiences and further offer even a window to the future. In the hands of the reader this book could provide an useful tool for the exploration of the application of information, knowledge and belief to some orthodontic topics and questions

VirtualIdentity : privacy preserving user profiling

User profiling from user generated content (UGC) is a common practice that supports the business models of many social media companies. Existing systems require that the UGC is fully exposed to the module that constructs the user profiles. In this paper we show that it is possible to build user profiles without ever accessing the user's original data, and without exposing the trained machine learning models for user profiling - which are the intellectual property of the company - to the users of the social media site. We present VirtualIdentity, an application that uses secure multi-party cryptographic protocols to detect the age, gender and personality traits of users by classifying their user-generated text and personal pictures with trained support vector machine models in a privacy preserving manner

Unsupervised inference approach to facial attractiveness

The perception of facial beauty is a complex phenomenon depending on many, detailed and global facial features influencing each other. In the machine learning community this problem is typically tackled as a problem of supervised inference. However, it has been conjectured that this approach does not capture the complexity of the phenomenon. A recent original experiment (Ib\'a\~nez-Berganza et al., Scientific Reports 9, 8364, 2019) allowed different human subjects to navigate the face-space and ``sculpt'' their preferred modification of a reference facial portrait. Here we present an unsupervised inference study of the set of sculpted facial vectors in that experiment. We first infer minimal, interpretable, and faithful probabilistic models (through Maximum Entropy and artificial neural networks) of the preferred facial variations, that capture the origin of the observed inter-subject diversity in the sculpted faces. The application of such generative models to the supervised classification of the gender of the sculpting subjects, reveals an astonishingly high prediction accuracy. This result suggests that much relevant information regarding the subjects may influence (and be elicited from) her/his facial preference criteria, in agreement with the multiple motive theory of attractiveness proposed in previous works.Comment: main article (10 pages, 4 figures) + supplementary information (22 pages, 10 figures). minor typos corrected. Federico Maggiore added as autho

Expectations Of Orthodontic Treatment In Adults: The Conduct In Orthodontist/patient Relationship.

The high demand for orthodontic treatment, evidenced over the last few decades, has been justified mainly by the greater importance given to facial esthetics, influencing individual's self esteem. However, the professional frequently does not meet all the patient's expectations, for not establishing good communication and not knowing about the critical points during orthodontic treatment. The aim of this study was to elucidate patients' desires and doubts regarding orthodontic treatment, by means of a survey applied to 60 adult patients. The analysis of results revealed that most individuals (38.3%) noticed treatment success after its conclusion. Occlusion deviation was pointed out by 66.7% as the main reason for seeking treatment, and esthetics ranked as second (with 48.3%). Treatment time was considered within the prediction by 46.7% of the interviewees and the results were judged as very good by 43.3%. The social relations of most participants were not affected by treatment (73.3%). Also, 58.3% of the interviewees reported pain as the main complaint and 53.3% found it difficult to use dental floss. Most participants saw the orthodontist as a professional who was concerned about their health (76.7%), and believed that he/she was more able to treat them (96.6%) when compared with the general practitioner. The orthodontist/patient relationship enables an understanding of the expectations regarding orthodontic treatment, resulting in greater motivation and cooperation, leading to a successful outcome.1888-9

Beauty in Snowflakes: Complexity and Visual Aesthetics

Experimental aesthetics research has been conducted since the nineteenth century. Interestingly, however, few studies have examined the perceived beauty of naturally shaped objects. In the current experiment, 204 participants were presented with a set of ten snowflake silhouettes that varied in complexity (perimeter relative to area); they were similarly presented with ten randomly-shaped, computer-generated, solid objects that also varied in complexity. For each stimulus set, the participants selected the single snowflake or object that was the most beautiful (Fechner’s method of choice). The results for the solid objects replicated the findings of earlier research: the most and least complex objects were chosen as the most beautiful. Moderately complex objects were rarely selected. The results for the snowflakes were different. For these visual stimuli, the least complex snowflakes were almost never chosen; only the complex snowflakes were perceived to be most beautiful, with the aesthetic preference increasing with increases in complexity