Search results for: facial attractiveness

Authors: Kyung-Ja Cho, Sun Jin Park

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This study examined what effective dimension affects facial attractiveness. Two orthogonal dimensions, sharp-soft and babyish-mature, were used to rate the levels of facial attractiveness in 20’s women. This research also investigated the sex difference on the effect of effective dimension of face on attractiveness. The test subjects composed of 15 males and 18 females. They looked 330 photos of women in 20s. Then they rated the levels of the effective dimensions of faces with sharp-soft and babyish-mature, and the attraction with charmless-charming. The respond forms were Likert scales, the answer was scored from 1 to 9. As a result of multiple regression analysis, the subject reported the milder and younger appearance as more attractive. Both male and female subjects showed the same evaluation. This result means that two effective dimensions have the effect on estimating attractiveness.

Keywords: affective dimension of faces, facial attractiveness, sharp-soft, babyish-mature

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Authors: Anas Ibrahim Yahaya, Christophe Soligo

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A substantial body of literature has reported on facial symmetry and asymmetry and their role in human mate choice. However, major gaps persist, with nearly all data originating from the WEIRD (Western, Educated, Industrialised, Rich and Developed) populations, and results remaining largely equivocal when compared across studies. This study is aimed at quantifying facial asymmetry from the 3D faces of the Hausa of northern Nigeria and also aimed at determining their (Hausa) perceptions and judgements of standardised facial images with different levels of asymmetry using questionnaires. Data were analysed using R-studio software and results indicated that individuals with lower levels of facial asymmetry (near facial symmetry) were perceived as more attractive, more suitable as marriage partners and more caring, whereas individuals with higher levels of facial asymmetry were perceived as more aggressive. The study conclusively asserts that all faces are asymmetric including the most beautiful ones, and the preference of less asymmetric faces was not just dependent on single facial trait, but rather on multiple facial traits; thus the study supports that physical attractiveness is not just an arbitrary social construct, but at least in part a cue to general health and possibly related to environmental context.

Keywords: face, asymmetry, symmetry, Hausa, preference

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Authors: Noha El Toukhy

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The ‘beauty is good” stereotype suggests that people perceive attractive people as having several positive characteristics. Likewise, an “anomalous-is-bad” stereotype is hypothesized to facilitate biases against people with anomalous or less attractive faces. Researchers integrated both into a stereotype content model, which is one of the frameworks used in this study to assess how facial anomalies influence people’s social attitudes and, specifically, people’s ratings of warmth and competence. The mind perception theory, as well as the assessment of animalistic and mechanistic dehumanization against facially anomalous people, are two further frameworks that we are using in this study. This study will test the hypothesis that people have negative attitudes towards people with facial anomalies. We also hypothesize that people have negative biases toward faces with visible differences compared to faces without such differences regardless of the specific type of anomaly, as well as that individual differences in psychological dispositions bear on the expression of the anomalous-is-bad stereotype. Using highly controlled and some never-before-used face stimuli, this pre-registered study examines whether moral character influences perceptions of attractiveness, warmth, and competence for facial anomalies.

Keywords: adolescents, attractiveness, competence, social attitudes, warmth

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Authors: Man N. M. Cheung

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In judging the attractiveness of female body shape, visual sense is one of the important means. The ratio and proportion of body shape influence the perception of female physical attractiveness. This study aims to examine visual perception of digital textile prints on a virtual 3D model in judging the attractiveness of the body shape. Also, investigate the influences when using different shape parameters and their relationships. Participants were asked to conduct a set of questionnaires with images to rank the attractiveness of the female body shape. Results showed that morphing the fabric prints with a certain ratio and combination of shape parameters - waist and hip, can enhance the attractiveness of the female body shape.

Keywords: digital printing, 3D body modeling, fashion print design, body shape attractiveness

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Authors: Naoya Ozaki, Takuya Watanabe, Ryosuke Matsumoto, Noriko Fukasawa

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In the metropolitan areas in Japan, in many stations, shopping areas are set up, and escalators and elevators are installed to make the stations be barrier-free. Further, many areas around the stations are being redeveloped. Railway business operators want to know how much effect these circumstances have on attractiveness of the station or number of passengers using the station. So, we performed a questionnaire survey of the station users in the metropolitan areas for finding factors to affect the attractiveness of stations. Then, based on the analysis of the survey, we developed a method to quantitatively evaluate attractiveness of the stations. We also developed an estimation method for number of passengers based on combination of attractiveness of the station quantitatively evaluated and the residential and labor population around the station. Then, we derived precise linear regression models estimating the attractiveness of the station and number of passengers of the station.

Keywords: attractiveness of the station, estimation method, number of passengers of the station, redevelopment around the station, renovation of the station

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Authors: Neha Singh, Ananya Arora

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Facial expression measurement plays a crucial role in the identification of emotion. Facial expression plays a key role in psychophysiology, neural bases, and emotional disorder, to name a few. The Facial Action Coding System (FACS) has proven to be the most efficient and widely used of the various systems used to describe facial expressions. Coders can manually code facial expressions with FACS and, by viewing video-recorded facial behaviour at a specified frame rate and slow motion, can decompose into action units (AUs). Action units are the most minor visually discriminable facial movements. FACS explicitly differentiates between facial actions and inferences about what the actions mean. Action units are the fundamental unit of FACS methodology. It is regarded as the standard measure for facial behaviour and finds its application in various fields of study beyond emotion science. These include facial neuromuscular disorders, neuroscience, computer vision, computer graphics and animation, and face encoding for digital processing. This paper discusses the conceptual basis for FACS, a numerical listing of discrete facial movements identified by the system, the system's psychometric evaluation, and the software's recommended training requirements.

Keywords: facial action, action units, coding, machine learning

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Authors: Bassam Band, Simon Freeman, Rohan Munir, Hisham Band

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Objective: To determine efficacy of facial physiotherapy provided for patients with facial nerve palsy. Design: Retrospective study Subjects: 54 patients diagnosed with Facial nerve palsy were included in the study after they met the selection criteria including unilateral facial paralysis and start of therapy twelve months after the onset of facial nerve palsy. Interventions: Patients received the treatment offered at a facial physiotherapy clinic consisting of: Trophic electrical stimulation, surface electromyography with biofeedback, neuromuscular re-education and myofascial release. Main measures: The Sunnybrook facial grading scale was used to evaluate the severity of facial paralysis. Results: This study demonstrated the positive impact of physiotherapy for patient with facial nerve palsy with improvement of 24.2% on the Sunnybrook facial grading score from a mean baseline of 34.2% to 58.2%. The greatest improvement looking at different causes was seen in patient who had reconstructive surgery post Acoustic Neuroma at 31.3%. Conclusion: The therapy shows significant improvement for patients with facial nerve palsy even when started 12 months post onset of paralysis across different causes. This highlights the benefit of this non-invasive technique in managing facial nerve paralysis and possibly preventing the need for surgery.

Keywords: facial nerve palsy, treatment, physiotherapy, bells palsy, acoustic neuroma, ramsey-hunt syndrome

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Authors: Alexandra Roy

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This research examines how physical and vocal attractiveness affect impressions of an applicant and whether these impressions are affected by gender or job type. Findings, based on two samples, indicate that individuals with less attractiveness voice and physical appearance were viewed as less suitable job applicants and as possessing more negative characteristics than those others. These negative impressions were pervasive and unaffected by either applicant gender or job type. Specifically, we found that job candidates with an attractive voice or physique were perceived as more extroverted, less agreeable, less conscientious, less trustworthy less competent, less sociable and less recruitable. Results are robust to various sensitivity checks.

Keywords: discrimination, nonverbal, hiring, attractiveness

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Authors: Elham Alaee, Mousa Shamsi, Hossein Ahmadi, Soroosh Nazem, Mohammad Hossein Sedaaghi

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Human face has a fundamental role in the appearance of individuals. So the importance of facial surgeries is undeniable. Thus, there is a need for the appropriate and accurate facial skin segmentation in order to extract different features. Since Fuzzy C-Means (FCM) clustering algorithm doesn’t work appropriately for noisy images and outliers, in this paper we exploit Possibilistic C-Means (PCM) algorithm in order to segment the facial skin. For this purpose, first, we convert facial images from RGB to YCbCr color space. To evaluate performance of the proposed algorithm, the database of Sahand University of Technology, Tabriz, Iran was used. In order to have a better understanding from the proposed algorithm; FCM and Expectation-Maximization (EM) algorithms are also used for facial skin segmentation. The proposed method shows better results than the other segmentation methods. Results include misclassification error (0.032) and the region’s area error (0.045) for the proposed algorithm.

Keywords: facial image, segmentation, PCM, FCM, skin error, facial surgery

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Authors: Marie Alaghband, Niloofar Yousefi, Ivan Garibay

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Facial expressions are important parts of both gesture and sign language recognition systems. Despite the recent advances in both fields, annotated facial expression datasets in the context of sign language are still scarce resources. In this manuscript, we introduce an annotated sequenced facial expression dataset in the context of sign language, comprising over 3000 facial images extracted from the daily news and weather forecast of the public tv-station PHOENIX. Unlike the majority of currently existing facial expression datasets, FePh provides sequenced semi-blurry facial images with different head poses, orientations, and movements. In addition, in the majority of images, identities are mouthing the words, which makes the data more challenging. To annotate this dataset we consider primary, secondary, and tertiary dyads of seven basic emotions of "sad", "surprise", "fear", "angry", "neutral", "disgust", and "happy". We also considered the "None" class if the image’s facial expression could not be described by any of the aforementioned emotions. Although we provide FePh as a facial expression dataset of signers in sign language, it has a wider application in gesture recognition and Human Computer Interaction (HCI) systems.

Keywords: annotated facial expression dataset, gesture recognition, sequenced facial expression dataset, sign language recognition

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Authors: Vesna Kirandziska, Nevena Ackovska, Ana Madevska Bogdanova

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The problem of emotion recognition is a challenging problem. It is still an open problem from the aspect of both intelligent systems and psychology. In this paper, both voice features and facial features are used for building an emotion recognition system. A Support Vector Machine classifiers are built by using raw data from video recordings. In this paper, the results obtained for the emotion recognition are given, and a discussion about the validity and the expressiveness of different emotions is presented. A comparison between the classifiers build from facial data only, voice data only and from the combination of both data is made here. The need for a better combination of the information from facial expression and voice data is argued.

Keywords: emotion recognition, facial recognition, signal processing, machine learning

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Authors: Jadisha Cornejo, Helio Pedrini

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Recognition of emotions based on facial expressions has received increasing attention from the scientific community over the last years. Several fields of applications can benefit from facial emotion recognition, such as behavior prediction, interpersonal relations, human-computer interactions, recommendation systems. In this work, we develop and analyze an emotion recognition framework based on facial expressions robust to occlusions through the Weber Local Descriptor (WLD). Initially, the occluded facial expressions are reconstructed following an extension approach of Robust Principal Component Analysis (RPCA). Then, WLD features are extracted from the facial expression representation, as well as Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG). The feature vector space is reduced using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). Finally, K-Nearest Neighbor (K-NN) and Support Vector Machine (SVM) classifiers are used to recognize the expressions. Experimental results on three public datasets demonstrated that the WLD representation achieved competitive accuracy rates for occluded and non-occluded facial expressions compared to other approaches available in the literature.

Keywords: emotion recognition, facial expression, occlusion, fiducial landmarks

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Authors: Fabiola M. Villalobos-Castaldi, Nicolás C. Kemper, Esther Rojas-Krugger, Laura G. Ramírez-Sánchez

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This paper presents the classification results about exploring the combination of a motion based approach with a local appearance method to describe the facial motion caused by the muscle contractions and expansions that are presented in facial expressions. The proposed feature extraction method take advantage of the knowledge related to which parts of the face reflects the highest deformations, so we selected 4 specific facial regions at which the appearance descriptor were applied. The most common used approaches for feature extraction are the holistic and the local strategies. In this work we present the results of using a local appearance approach estimating the correlation coefficient to the 4 corresponding landmark-localized facial templates of the expression face related to the neutral face. The results let us to probe how the proposed motion estimation scheme based on the local appearance correlation computation can simply and intuitively measure the motion parameters for some of the most relevant facial regions and how these parameters can be used to recognize facial expressions automatically.

Keywords: facial expression recognition system, feature extraction, local-appearance method, motion-based approach

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Authors: Rahul Mohite, Lahcen Ouarbya

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This paper focuses on the interplay between humans and computer systems and the ability of these systems to understand and respond to human emotions, including non-verbal communication. Current emotion recognition systems are based solely on either facial or verbal expressions. The limitation of these systems is that it requires large training data sets. The paper proposes a system for recognizing human emotions that combines both speech and emotion recognition. The system utilizes advanced techniques such as deep learning and image recognition to identify facial expressions and comprehend emotions. The results show that the proposed system, based on the combination of facial expression and speech, outperforms existing ones, which are based solely either on facial or verbal expressions. The proposed system detects human emotion with an accuracy of 86%, whereas the existing systems have an accuracy of 70% using verbal expression only and 76% using facial expression only. In this paper, the increasing significance and demand for facial recognition technology in emotion recognition are also discussed.

Keywords: facial reputation, expression reputation, deep gaining knowledge of, photo reputation, facial technology, sign processing, photo type

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Authors: Ksheeraj Sai Vepuri, Nada Attar

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We as humans use words with accompanying visual and facial cues to communicate effectively. Classifying facial emotion using computer vision methodologies has been an active research area in the computer vision field. In this paper, we propose a simple method for facial expression recognition that enhances accuracy. We tested our method on the FER-2013 dataset that contains static images. Instead of using Histogram equalization to preprocess the dataset, we used Unsharp Mask to emphasize texture and details and sharpened the edges. We also used ImageDataGenerator from Keras library for data augmentation. Then we used Convolutional Neural Networks (CNN) model to classify the images into 7 different facial expressions, yielding an accuracy of 69.46% on the test set. Our results show that using image preprocessing such as the sharpening technique for a CNN model can improve the performance, even when the CNN model is relatively simple.

Keywords: facial expression recognittion, image preprocessing, deep learning, CNN

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Authors: Sarah Sayed El- Tawab, Emmanuel Kamal Azix Saba

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Objectives: Somatosensory blink reflex (SBR) is an eye blink response obtained from electrical stimulation of peripheral nerves or skin area of the body. It has been studied in various neurological diseases as well as among healthy subjects in different population. We designed this study to detect SBR positivity in patients with facial palsy and patients with post facial syndrome, to relate the facial palsy severity and the presence of SBR, and to associate between trigeminal BR changes and SBR positivity in peripheral facial palsy patients. Methods: 50 patients with peripheral facial palsy and post-facial syndrome 31 age and gender matched healthy volunteers were enrolled to this study. Facial motor conduction studies, trigeminal BR, and SBR were studied in all. Results: SBR was elicited in 67.7% of normal subjects, in 68% of PFS group, and in 32% of PFP group. On the non-paralytic side SBR was found in 28% by paralyzed side stimulation and in 24% by healthy side stimulation among PFP patients. For PFS group SBR was found on the non- paralytic side in 48%. Bilateral SBR elicitability was higher than its unilateral elicitability. Conclusion: Increased brainstem interneurons excitability is not essential to generate SBR. The hypothetical sensory-motor gating mechanism is responsible for SBR generation.

Keywords: somatosensory evoked blink reflex, post facial syndrome, blink reflex, enchanced gain

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Authors: Dawood Al Chanti, Alice Caplier

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Sparse representations of signals have received a great deal of attention in recent years. In this paper, the interest of using sparse representation as a mean for performing sparse discriminative analysis between spontaneous facial expressions is demonstrated. An automatic facial expressions recognition system is presented. It uses a KSVD-SVM approach which is made of three main stages: A pre-processing and feature extraction stage, which solves the problem of shared subspace distribution based on the random projection theory, to obtain low dimensional discriminative and reconstructive features; A dictionary learning and sparse coding stage, which uses the KSVD model to learn discriminative under or over dictionaries for sparse coding; Finally a classification stage, which uses a SVM classifier for facial expressions recognition. Our main concern is to be able to recognize non-basic affective states and non-acted expressions. Extensive experiments on the JAFFE static acted facial expressions database but also on the DynEmo dynamic spontaneous facial expressions database exhibit very good recognition rates.

Keywords: dictionary learning, random projection, pose and spontaneous facial expression, sparse representation

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Authors: Natalia Polkanova, Sergey Kazakov

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In the research, we proposed the set of factors of tourist destinations attractiveness in Spain and determined the factors that have the greatest impact on the positive perception of the tourist destination by Russian tourists; also, we examined what factors create the willingness for Russians to recommend this tourist destination to their friends and relatives. The tourists' comments on the Russian travel sites have been analyzed in order to determine the frequency of attractiveness characteristics references. Additionally, the study will reflect the relationship of variables.

Keywords: tourism destination, destination attractiveness, destination competitiveness, content analysis, unstructured image

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Authors: Valentina Zhang

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While facial expression is a complex and individualized behavior, all facial emotion recognition (FER) systems known to us rely on a single facial representation and are trained on universal data. We conjecture that: (i) different facial representations can provide different, sometimes complementing views of emotions; (ii) when employed collectively in a discussion group setting, they enable more accurate emotion reading which is highly desirable in autism care and other applications context sensitive to errors. In this paper, we first study FER using pixel-based DL vs semantics-based DL in the context of deepfake videos. Our experiment indicates that while the semantics-trained model performs better with articulated facial feature changes, the pixel-trained model outperforms on subtle or rare facial expressions. Armed with these findings, we have constructed an adaptive FER system learning from both types of models for dyadic or small interacting groups and further leveraging the synthesized group emotions as the ground truth for individualized FER training. Using a collection of group conversation videos, we demonstrate that FER accuracy and personalization can benefit from such an approach.

Keywords: neurodivergence care, facial emotion recognition, deep learning, ground truth for supervised learning

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Authors: Nouha Khediri, Mohammed Ben Ammar, Monji Kherallah

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Recently, facial emotion recognition (FER) has become increasingly essential to understand the state of the human mind. Accurately classifying emotion from the face is a challenging task. In this paper, we present a facial emotion recognition approach named CV-FER, benefiting from deep learning, especially CNN and VGG16. First, the data is pre-processed with data cleaning and data rotation. Then, we augment the data and proceed to our FER model, which contains five convolutions layers and five pooling layers. Finally, a softmax classifier is used in the output layer to recognize emotions. Based on the above contents, this paper reviews the works of facial emotion recognition based on deep learning. Experiments show that our model outperforms the other methods using the same FER2013 database and yields a recognition rate of 92%. We also put forward some suggestions for future work.

Keywords: CNN, deep-learning, facial emotion recognition, machine learning

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Authors: Yi Shan Wu, Ting Hsuan Wu, Li Wei Cheng, Pei Yu Guo

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Given the fiercely competitive environment, human capital is one of the most valuable assets in a commercial enterprise. Therefore, developing strategies to acquire more talents is crucial. Talents are mainly attracted by both internal and external employer brands as well as by the messages conveyed from the employer image. This not only manifests the importance of a brand and an image of an organization but shows people might be affected by their personal values when assessing an organization as an employer. The goal of the present study is to examine the association between employer brand, employer image, and the likelihood of increasing organizational attractiveness. In addition, we draw from social identity theory to propose value congruence may affect the relationship between employer brand and employer image. Data was collected from those people who only worked less than a year in the industry via an online survey (N=209). The results show that employer image partly mediates the effect of employer brand on organizational attractiveness. In addition, the results also suggest that value congruence does not moderate the relationship between employer brand and employer image. These findings explain why building a good employer brand could enhance organization attractiveness and indicate there should be other factors that may affect employer image building, offering directions for future research.

Keywords: organizational attractiveness, employer brand, employer image, value congruence

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Authors: An Guo, Hieyong Jeong, Tianyi Wang, Na Li, Yuko Ohno

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Acupuncture, known as sensory simulation, has been used to treat various disorders for thousands of years. However, present studies had not addressed approaches for noninvasive measurement in order to evaluate therapeutic effect of acupuncture. The purpose of this study is to propose a noninvasive method to evaluate acupuncture by measuring facial temperature through thermal image. Three human subjects were recruited in this study. Each subject received acupuncture therapy for 30 mins. Acupuncture needles (Ø0.16 x 30 mm) were inserted into Baihui point (DU20), Neiguan points (PC6) and Taichong points (LR3), acupuncture needles (Ø0.18 x 39 mm) were inserted into Tanzhong point (RN17), Zusanli points (ST36) and Yinlingquan points (SP9). Facial temperature was recorded by an infrared thermometer. Acupuncture therapeutic effect was compared pre- and post-acupuncture. Experiment results demonstrated that facial temperature changed according to acupuncture therapeutic effect. It was concluded that proposed method showed high potential to evaluate acupuncture by noninvasive measurement of facial temperature.

Keywords: acupuncture, facial temperature, noninvasive evaluation, thermal image

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Authors: Mehdi Seifbarghy, Zahra Nasiri

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Competitive location problem deals with locating new facilities to provide a service (or goods) to the customers of a given geographical area where other facilities (competitors) offering the same service are already present. The new facilities will have to compete with the existing facilities for capturing the market share. This paper proposes a new model to maximize the market share in which customers choose the facilities based on traveling time, waiting time and attractiveness. The attractiveness of a facility is considered as a parameter in the model. A heuristic is proposed to solve the problem.

Keywords: competitive location, market share, facility attractiveness, heuristic

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Authors: Ashutosh Mishra, Nikhil Goyal

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A 3D facial emotion recognition model based on deep learning is proposed in this paper. Two convolution layers and a pooling layer are employed in the deep learning architecture. After the convolution process, the pooling is finished. The probabilities for various classes of human faces are calculated using the sigmoid activation function. To verify the efficiency of deep learning-based systems, a set of faces. The Kaggle dataset is used to verify the accuracy of a deep learning-based face recognition model. The model's accuracy is about 65 percent, which is lower than that of other facial expression recognition techniques. Despite significant gains in representation precision due to the nonlinearity of profound image representations.

Keywords: facial recognition, computational intelligence, convolutional neural network, depth map

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Authors: Amir Feily, Hazhir Shahmoradi Akram, Mojtaba Ghaedi, Farshid Javdani, Naser Hatami, Navid Kalani, Mohammad Zarenezhad

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Background: Filler-induced facial skin ischemia is a potential complication of dermal filler injections that can result in tissue damage and necrosis. Nitroglycerin has been suggested as a treatment option due to its vasodilatory effects, but its efficacy in this context is unclear. Methods: A narrative review was conducted to examine the available evidence on the efficacy of nitroglycerin in filler-induced facial skin ischemia. Relevant studies were identified through a search of electronic databases and manual searching of reference lists. Results: The review found limited evidence supporting the efficacy of nitroglycerin in this context. While there were case reports where the combination of nitroglycerin and hyaluronidase was successful in treating filler-induced facial skin ischemia, there was only one case report where nitroglycerin alone was successful. Furthermore, a rat model did not demonstrate any benefits of nitroglycerin and showed harmful results. Conclusion: The evidence regarding the efficacy of nitroglycerin in filler-induced facial skin ischemia is inconclusive and seems to be against its application. Further research is needed to determine the effectiveness of nitroglycerin alone and in combination with other treatments for this condition. Clinicians should consider limited evidence bases when deciding on treatment options for patients with filler-induced facial skin ischemia.

Keywords: nitroglycerin, facial, skin ischemia, fillers, efficacy, narrative review

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Authors: Daniia Nigmatullina, Vlada Kugurakova, Maxim Talanov

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We present a methodology and our plans of anthropomorphic social agent visualization. That includes creation of three-dimensional model of the virtual companion's head and its facial expressions. Talking Head is a cross-disciplinary project of developing of the human-machine interface with cognitive functions. During the creation of a realistic humanoid robot or a character, there might be the ‘uncanny valley’ problem. We think about this phenomenon and its possible causes. We are going to overcome the ‘uncanny valley’ by increasing of realism. This article discusses issues that should be considered when creating highly realistic characters (particularly the head), their facial expressions and speech visualization.

Keywords: anthropomorphic social agent, facial animation, uncanny valley, visualization, 3D modeling

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Authors: Nigar Sultanova

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Facial morphology is a constant topic of concern for clinicians. When anthropometric methods were introduced into clinical practice to quantify changes in the craniofacial framework, features distinguishing various ethnic group were discovered. Normative data of facial measurements are indispensable to precise determination of the degree of deviations from normal. Establish the reference range of facial proportions in Azerbaijan population by anthropometric measurements of craniofacial complex. The study group consisted of 350 healthy young subjects, 175 males and 175 females, 18 to 25 years of age, from 7 different regions of Azerbaijan. The anthropometric examination was performed according to L.Farkas's method with our modification. In order to determine the morphologic characteristics of seven regions of the craniofacial complex 42 anthropometric measurements were selected. The anthropometric examination. Included the usage of 33 anthropometric landmarks. The 80 indices of the facial proportions, suggested by Farkas and Munro, were calculated: head -10, face - 23, nose - 23, lips - 9, orbits - 11, ears - 4. The date base of the North American white population was used as a reference group. Anthropometric measurements of facial proportions in Azerbaijan population revealed a significant difference between mеn and womеn, according to sexual dimorphism. In comparison with North American whites, considerable differences of facial proportions were observed in the head, face, orbits, labio-oral, nose and ear region. However, in women of the Azerbaijani population, 29 out of 80 proportion indices were similar to the proportions of NAW women. In the men of the Azerbaijani population, 27 out of 80 proportion indices did not reveal a statistically significant difference from the proportions of NAW men. Estimation of the reference range of facial proportions in Azerbaijan population migth be helpful to formulate surgical plan in treatment of congenital or post-traumatic facial deformities successfully.

Keywords: facial morphology, anthropometry, indices of proportion, measurement

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Authors: Faizan Tariq, Moayid Ali Zaidi

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Facial emotion recognition algorithms are expanding rapidly now a day. People are using different algorithms with different combinations to generate best results. There are six basic emotions which are being studied in this area. Author tried to recognize the facial expressions using object detector algorithms instead of traditional algorithms. Two object detection algorithms were chosen which are Faster R-CNN and YOLO. For pre-processing we used image rotation and batch normalization. The dataset I have chosen for the experiments is Static Facial Expression in Wild (SFEW). Our approach worked well but there is still a lot of room to improve it, which will be a future direction.

Keywords: face recognition, emotion recognition, deep learning, CNN

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Authors: Shantanu Vyas, Neerja Meena

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Facial infiltrating lipomatosis is a rare lipomatous lesion, first described by Slavin in 1983. It is a benign pseudotumor pathology. It corresponds to a non-encapsulated collection of mature adipocytes infiltrating the local tissue and hyperplasia of underlying bone leading to a craniofacial deformity. Very few cases have been reported in the literature. We report the case of a 19-year-old female patient, who was consulted for a swelling of the right hemiface progressively evolving since birth. Physical examination revealed facial asymmetry. On palpation, the mass was soft, painless, not compressible, not pulsatile, not fluctuating. In view of the asymptomatic nature and slow progression of the lesion, a lipomatous tumour, namely lipoma, was suggested. CT scan image shows a hyperplastic subcutaneous fat on the right hemiface. On the right jugal and temporal areas, there is a subcutaneous formation of fatty density, poorly limited, with no detectable peripheral capsule. It merges with the adjacent fat. In the bone window, there was a hyperplasia of underlying bone. Facial lipomatosis infiltration of the face is a benign pseudotumor pathology. As a result, it can be confused with other disorders, in particular, hemifacial hyperplasia. Combination of physical and radiological findings can establish the diagnosis. Surgical treatment is done for cosmetic purposes.

Keywords: cosmetic correction and facial assemetry, aesthetic results, facial infiltration, surgery

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Authors: S. Kherchaoui, A. Houacine

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This paper presents a facial expression recognition system. It performs identification and classification of the seven basic expressions; happy, surprise, fear, disgust, sadness, anger, and neutral states. It consists of three main parts. The first one is the detection of a face and the corresponding facial features to extract the most expressive portion of the face, followed by a normalization of the region of interest. Then calculus of curvelet coefficients is performed with dimensionality reduction through principal component analysis. The resulting coefficients are combined with two ratios; mouth ratio and face edge ratio to constitute the whole feature vector. The third step is the classification of the emotional state using the SVM method in the feature space.

Keywords: facial expression identification, curvelet coefficient, support vector machine (SVM), recognition system

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