24,768 research outputs found

    The analysis of facial beauty: an emerging area of research in pattern analysis

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    Much research presented recently supports the idea that the human perception of attractiveness is data-driven and largely irrespective of the perceiver. This suggests using pattern analysis techniques for beauty analysis. Several scientific papers on this subject are appearing in image processing, computer vision and pattern analysis contexts, or use techniques of these areas. In this paper, we will survey the recent studies on automatic analysis of facial beauty, and discuss research lines and practical application

    A New Computer-aided Technique for Planning the Aesthetic Outcome of Plastic Surgery

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    Plastic surgery plays a major role in today health care. Planning plastic face surgery requires dealing with the elusive concept of attractiveness for evaluating feasible beautification of a particular face. The existing computer tools essentially allow to manually warp 2D images or 3D face scans, in order to produce images simulating possible surgery outcomes. How to manipulate faces, as well as the evaluation of the results, are left to the surgeon's judgement. We propose a new quantitative approach able to automatically suggest effective patient-specific improvements of facial attractiveness. The general idea is to compare the face of the patient with a large database of attractive faces, excluding the facial feature to be improved. Then, the feature of the faces more similar is applied, with a suitable morphing, to the face of the patient. In this paper we present a first application of the general idea in the field of nose surgery. Aesthetically effective rhinoplasty is suggested on the base of the entire face profile, a very important 2D feature for rating face attractivenes

    A New 3D Tool for Planning Plastic Surgery

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    Face plastic surgery (PS) plays a major role in today medicine. Both for reconstructive and cosmetic surgery, achieving harmony of facial features is an important, if not the major goal. Several systems have been proposed for presenting to patient and surgeon possible outcomes of the surgical procedure. In this paper, we present a new 3D system able to automatically suggest, for selected facial features as nose, chin, etc, shapes that aesthetically match the patient's face. The basic idea is suggesting shape changes aimed to approach similar but more harmonious faces. To this goal, our system compares the 3D scan of the patient with a database of scans of harmonious faces, excluding the feature to be corrected. Then, the corresponding features of the k most similar harmonious faces, as well as their average, are suitably pasted onto the patient's face, producing k+1 aesthetically effective surgery simulations. The system has been fully implemented and tested. To demonstrate the system, a 3D database of harmonious faces has been collected and a number of PS treatments have been simulated. The ratings of the outcomes of the simulations, provided by panels of human judges, show that the system and the underlying idea are effectiv

    Facial visualizations of women’s voices suggest a cross-modality preference for femininity

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    Women with higher-pitched voices and more feminine facial features are commonly judged as being more attractive than are women with lower-pitched voices and less feminine faces, possibly because both features are affected by (age-related) variations in endocrine status. These results are primarily derived from investigations of perceptions of variations in single-modality stimuli (i.e., faces or voices) in samples of young adult women. In the present study we sought to test whether male and female perceptions of women’s voices affect visual representations of facial femininity. Eighty men and women judged voice recordings of 10 young girls (11-15 years), 10 adult women (19-28 years) and 10 peri-/post-menopausal women (50-64 years) on age, attractiveness, and femininity. Another 80 men and women were asked to indicate the face they think each voice corresponded to using a video that gradually changed from a masculine looking male face into a feminine looking female face. Both male and female participants perceived voices of young girls and adult women to be significantly younger, more attractive and feminine than those of peri-/post-menopausal women. Hearing young girls’ and adult women’s voices resulted in both men and women selecting faces that differed markedly in apparent femininity from those associated with peri-/post-menopausal women’s voices. Voices of young girls had the strongest effect on visualizations of facial femininity. Our results suggest a cross-modal preference for women’s vocal and facial femininity, which depends on female age and is independent of the perceiver’s sex

    Some like it hot - visual guidance for preference prediction

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    For people first impressions of someone are of determining importance. They are hard to alter through further information. This begs the question if a computer can reach the same judgement. Earlier research has already pointed out that age, gender, and average attractiveness can be estimated with reasonable precision. We improve the state-of-the-art, but also predict - based on someone's known preferences - how much that particular person is attracted to a novel face. Our computational pipeline comprises a face detector, convolutional neural networks for the extraction of deep features, standard support vector regression for gender, age and facial beauty, and - as the main novelties - visual regularized collaborative filtering to infer inter-person preferences as well as a novel regression technique for handling visual queries without rating history. We validate the method using a very large dataset from a dating site as well as images from celebrities. Our experiments yield convincing results, i.e. we predict 76% of the ratings correctly solely based on an image, and reveal some sociologically relevant conclusions. We also validate our collaborative filtering solution on the standard MovieLens rating dataset, augmented with movie posters, to predict an individual's movie rating. We demonstrate our algorithms on howhot.io which went viral around the Internet with more than 50 million pictures evaluated in the first month.Comment: accepted for publication at CVPR 201

    Crowd-sourced Photographic Content for Urban Recreational Route Planning

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    Routing services are able to provide travel directions for users of all modes of transport. Most of them are focusing on functional journeys (i.e. journeys linking given origin and destination with minimum cost) while paying less attention to recreational trips, in particular leisure walks in an urban context. These walks are additionally predefined by time or distance and as their purpose is the process of walking itself, the attractiveness of areas that are passed by can be an important factor in route selection. This factor is hard to be formalised and requires a reliable source of information, covering the entire street network. Previous research shows that crowd-sourced data available from photo-sharing services has a potential for being a measure of space attractiveness, thus becoming a base for a routing system that suggests leisure walks, and ongoing PhD research aims to build such system. This paper demonstrates findings on four investigated data sources (Flickr, Panoramio, Picasa and Geograph) in Central London and discusses the requirements to the algorithm that is going to be implemented in the second half of this PhD research. Visual analytics was chosen as a method for understanding and comparing obtained datasets that contain hundreds of thousands records. Interactive software was developed to find a number of problems, as well as to estimate the suitability of the sources in general. It was concluded that Picasa and Geograph have problems making them less suitable for further research while Panoramio and Flickr require filtering to remove photographs that do not contribute to understanding of local attractiveness. Based on this analysis a number of filtering methods were proposed in order to improve the quality of datasets and thus provide a more reliable measure to support urban recreational routing

    On the assumptions that we make about the world around us : a conceptual framework for feature transformation effects

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    Various phenomena such as halo effects, spontaneous trait inferences, and evaluative conditioning have in common that assumptions about object features (e.g., whether a person is intelligent or likeable) are influenced by other object features (e.g., whether that person is attractive or co-occurs with other liked persons). Surprisingly, these phenomena have rarely been related to each other, most likely because different phenomena are described using different terms. To overcome this barrier, we put forward a conceptual framework that can be used to describe a wide range of these phenomena. After introducing the four core concepts of the framework, we illustrate how it can be applied to various phenomena. Doing so helps to reveal similarities and differences between those phenomena, thus improving communication and promoting interactions between different areas of research. Finally, we illustrate the generative power of the framework by discussing some of the new research questions that it highlights

    Why is low waist-to-chest ratio attractive in males? The mediating roles of perceived dominance, fitness, and protection ability

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    Past research suggests that a lower waist-to-chest ratio (WCR) in men (i.e., narrower waist and broader chest) is viewed as attractive by women. However, little work has directly examined why low WCRs are preferred. The current work merged insights from theory and past research to develop a model examining perceived dominance, fitness, and protection ability as mediators of to WCR-attractiveness relationship. These mediators and their link to both short-term (sexual) and long-term (relational) attractiveness were simultaneously tested by having 151 women rate one of 15 avatars, created from 3D body scans. Men with lower WCR were perceived as more physically dominant, physically fit, and better able to protect loved ones; these characteristics differentially mediated the effect of WCR on short-term, long-term, and general attractiveness ratings. Greater understanding of the judgments women form regarding WCR may yield insights into motivations by men to manipulate their body image
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