scholarly journals Effect of turning-Q laser in combination with topical Chuangfukang collagen mask to improve facial appearance, greenish brown birthmark area and color depth of patients with facial greenish brown birthmark

2021 ◽  
Author(s):  
Chu-na ZHENG ◽  
Peiping WANG ◽  
Dongying YAO ◽  
Xiaojuan FANG ◽  
Jianglin WU ◽  
...  
Keyword(s):  
Facial Appearance ◽  
Color Depth

The Gender Typicality of Faces and Its Impact on Visual Processing and on Hiring Decisions

2013 ◽  
Vol 60 (6) ◽  
pp. 444-452 ◽  
Author(s):  
Lisa von Stockhausen ◽  
Sara Koeser ◽  
Sabine Sczesny
Keyword(s):  
Visual Processing ◽  
Past Research ◽  
Visual Exploration ◽  
Facial Appearance ◽  
Leadership Roles ◽  
Hiring Decisions ◽  
Leadership Selection ◽  
Gender Typicality ◽  
Second Stage ◽  
The Feminine

Past research has shown that the gender typicality of applicants’ faces affects leadership selection irrespective of a candidate’s gender: A masculine facial appearance is congruent with masculine-typed leadership roles, thus masculine-looking applicants are hired more certainly than feminine-looking ones. In the present study, we extended this line of research by investigating hiring decisions for both masculine- and feminine-typed professional roles. Furthermore, we used eye tracking to examine the visual exploration of applicants’ portraits. Our results indicate that masculine-looking applicants were favored for the masculine-typed role (leader) and feminine-looking applicants for the feminine-typed role (team member). Eye movement patterns showed that information about gender category and facial appearance was integrated during first fixations of the portraits. Hiring decisions, however, were not based on this initial analysis, but occurred at a second stage, when the portrait was viewed in the context of considering the applicant for a specific job.

Children use targets’ facial appearance to guide and predict social behavior.

2019 ◽  
Vol 55 (7) ◽  
pp. 1400-1413 ◽  
Author(s):  
Tessa E. S. Charlesworth ◽  
Sa-kiera T. J. Hudson ◽  
Emily J. Cogsdill ◽  
Elizabeth S. Spelke ◽  
Mahzarin R. Banaji
Keyword(s):  
Social Behavior ◽  
Facial Appearance

The accuracy of inferences about criminality based on facial appearance.

2011 ◽  
Vol 5 (1) ◽  
pp. 66-91 ◽  
Author(s):  
Jeffrey M. Valla ◽  
Stephen J. Ceci ◽  
Wendy M. Williams
Keyword(s):  
Facial Appearance

FACE RECOGNITION USING FUZZY INFERENCE SYSTEM

2009 ◽  
Vol 8 (3) ◽  
pp. 887-897
Author(s):  
Vishal Paika ◽  
Er. Pankaj Bhambri
Keyword(s):  
Neural Networks ◽  
Fuzzy Inference ◽  
Facial Features ◽  
Facial Appearance ◽  
Feature Points ◽  
Inference System ◽  
Detection Techniques ◽  
The Face ◽  
Hair Style ◽  
Facial Images

The face is the feature which distinguishes a person. Facial appearance is vital for human recognition. It has certain features like forehead, skin, eyes, ears, nose, cheeks, mouth, lip, teeth etc which helps us, humans, to recognize a particular face from millions of faces even after a large span of time and despite large changes in their appearance due to ageing, expression, viewing conditions and distractions such as disfigurement of face, scars, beard or hair style. A face is not merely a set of facial features but is rather but is rather something meaningful in its form.In this paper, depending on the various facial features, a system is designed to recognize them. To reveal the outline of the face, eyes, ears, nose, teeth etc different edge detection techniques have been used. These features are extracted in the term of distance between important feature points. The feature set obtained is then normalized and are feed to artificial neural networks so as to train them for reorganization of facial images.

Smoking status and attractiveness among identical twins discordant for smoking

2017 ◽  
Author(s):  
Andy Skinner ◽  
Andy ◽  
Ian Penton-Voak ◽  
Marcus Robert Munafo
Keyword(s):  
Behaviour Change ◽  
Smoking Status ◽  
Smoking Behaviour ◽  
Identical Twins ◽  
Facial Appearance ◽  
Same Sex ◽  
Facial Aging ◽  
Male And Female ◽  
Separate Sample ◽  
Behaviour Change Interventions

Background and aims: Smoking is associated with negative health of skin and increased signs of facial aging. We aimed to address two questions about smoking and appearance: 1) how does smoking affect the attractiveness of faces, and 2) does facial appearance alone provide an indication of smoking status?Methods: Faces of identical twins discordant for smoking were averaged to make male and female smoking and non-smoking prototypes faces. In Task 1, we presented same sex smoking and non-smoking prototypes side-by-side and participants (n=590) indicated which face was more attractive. Participants were blind to prototype smoking status. In Task 2 a separate sample (n=580) indicated which prototype was the smoker.Results: In Task 1 both male and female participants judged non-smoking prototypes more attractive, irrespective of the sex of the prototype face. In Task 2, both male and female participants selected the smoking prototype as the smoker more often, again irrespective of the sex of the prototype face.Conclusions: Our findings provide evidence that smoking may negatively impact facial appearance, and that facial appearance alone may be sufficient to indicate smoking status. We discuss the possible use of these findings in smoking behaviour change interventions.

Towards a New Approach to Cross-Cultural Distinctiveness and Typicality of Human Faces: The Cross-Group Typicality/Distinctiveness Metric

2018 ◽  
Author(s):  
Karel Kleisner ◽  
Šimon Pokorný ◽  
Selahattin Adil Saribay
Keyword(s):  
Cross Cultural ◽  
Facial Appearance ◽  
Alternative Measure ◽  
Home Culture ◽  
Facial Stimuli ◽  
The Two Cultures ◽  
Potential Applications ◽  
The Individual ◽  
Human Faces ◽  
Ingroup Outgroup

In present research, we took advantage of geometric morphometrics to propose a data-driven method for estimating the individual degree of facial typicality/distinctiveness for cross-cultural (and other cross-group) comparisons. Looking like a stranger in one’s home culture may be somewhat stressful. The same facial appearance, however, might become advantageous within an outgroup population. To address this fit between facial appearance and cultural setting, we propose a simple measure of distinctiveness/typicality based on position of an individual along the axis connecting the facial averages of two populations under comparison. The more distant a face is from its ingroup population mean towards the outgroup mean the more distinct it is (vis-à-vis the ingroup) and the more it resembles the outgroup standards. We compared this new measure with an alternative measure based on distance from outgroup mean. The new measure showed stronger association with rated facial distinctiveness than distance from outgroup mean. Subsequently, we manipulated facial stimuli to reflect different levels of ingroup-outgroup distinctiveness and tested them in one of the target cultures. Perceivers were able to successfully distinguish outgroup from ingroup faces in a two-alternative forced-choice task. There was also some evidence that this task was harder when the two faces were closer along the axis connecting the facial averages from the two cultures. Future directions and potential applications of our proposed approach are discussed.

scholarly journals Iranian kinect face database (IKFDB): a color-depth based face database collected by kinect v.2 sensor

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Seyed Muhammad Hossein Mousavi ◽  
S. Younes Mirinezhad
Keyword(s):  
Neural Network ◽  
Facial Expression ◽  
Facial Expression Recognition ◽  
Depth Image ◽  
Sensor Technology ◽  
Support Vector ◽  
Expression Recognition ◽  
Face Database ◽  
Depth Data ◽  
Color Depth

AbstractThis study presents a new color-depth based face database gathered from different genders and age ranges from Iranian subjects. Using suitable databases, it is possible to validate and assess available methods in different research fields. This database has application in different fields such as face recognition, age estimation and Facial Expression Recognition and Facial Micro Expressions Recognition. Image databases based on their size and resolution are mostly large. Color images usually consist of three channels namely Red, Green and Blue. But in the last decade, another aspect of image type has emerged, named “depth image”. Depth images are used in calculating range and distance between objects and the sensor. Depending on the depth sensor technology, it is possible to acquire range data differently. Kinect sensor version 2 is capable of acquiring color and depth data simultaneously. Facial expression recognition is an important field in image processing, which has multiple uses from animation to psychology. Currently, there is a few numbers of color-depth (RGB-D) facial micro expressions recognition databases existing. With adding depth data to color data, the accuracy of final recognition will be increased. Due to the shortage of color-depth based facial expression databases and some weakness in available ones, a new and almost perfect RGB-D face database is presented in this paper, covering Middle-Eastern face type. In the validation section, the database will be compared with some famous benchmark face databases. For evaluation, Histogram Oriented Gradients features are extracted, and classification algorithms such as Support Vector Machine, Multi-Layer Neural Network and a deep learning method, called Convolutional Neural Network or are employed. The results are so promising.

scholarly journals More human than human: a Turing test for photographed faces

2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Jet Gabrielle Sanders ◽  
Yoshiyuki Ueda ◽  
Sakiko Yoshikawa ◽  
Rob Jenkins
Keyword(s):  
Social Context ◽  
Personal Identity ◽  
Error Rate ◽  
Turing Test ◽  
Perceptual Task ◽  
Viewing Time ◽  
Facial Appearance ◽  
Theoretical Interest ◽  
Significant Performance ◽  
Recent Experimental Work

Abstract Background Recent experimental work has shown that hyper-realistic face masks can pass for real faces during live viewing. However, live viewing embeds the perceptual task (mask detection) in a powerful social context that may influence respondents’ behaviour. To remove this social context, we assessed viewers’ ability to distinguish photos of hyper-realistic masks from photos of real faces in a computerised two-alternative forced choice (2AFC) procedure. Results In experiment 1 (N = 120), we observed an error rate of 33% when viewing time was restricted to 500 ms. In experiment 2 (N = 120), we observed an error rate of 20% when viewing time was unlimited. In both experiments we saw a significant performance cost for other-race comparisons relative to own-race comparisons. Conclusions We conclude that viewers could not reliably distinguish hyper-realistic face masks from real faces in photographic presentations. As well as its theoretical interest, failure to detect synthetic faces has important implications for security and crime prevention, which often rely on facial appearance and personal identity being related.

Sign in / Sign up

Export Citation Format

Share Document