Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 759

Search results for: facial surgery

759 Management of Facial Nerve Palsy Following Physiotherapy

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


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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758 Automatic Facial Skin Segmentation Using Possibilistic C-Means Algorithm for Evaluation of Facial Surgeries

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


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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757 Pre-Operative Tool for Facial-Post-Surgical Estimation and Detection

Authors: Ayat E. Ali, Christeen R. Aziz, Merna A. Helmy, Mohammed M. Malek, Sherif H. El-Gohary


Goal: Purpose of the project was to make a plastic surgery prediction by using pre-operative images for the plastic surgeries’ patients and to show this prediction on a screen to compare between the current case and the appearance after the surgery. Methods: To this aim, we implemented a software which used data from the internet for facial skin diseases, skin burns, pre-and post-images for plastic surgeries then the post- surgical prediction is done by using K-nearest neighbor (KNN). So we designed and fabricated a smart mirror divided into two parts a screen and a reflective mirror so patient's pre- and post-appearance will be showed at the same time. Results: We worked on some skin diseases like vitiligo, skin burns and wrinkles. We classified the three degrees of burns using KNN classifier with accuracy 60%. We also succeeded in segmenting the area of vitiligo. Our future work will include working on more skin diseases, classify them and give a prediction for the look after the surgery. Also we will go deeper into facial deformities and plastic surgeries like nose reshaping and face slim down. Conclusion: Our project will give a prediction relates strongly to the real look after surgery and decrease different diagnoses among doctors. Significance: The mirror may have broad societal appeal as it will make the distance between patient's satisfaction and the medical standards smaller.

Keywords: k-nearest neighbor (knn), face detection, vitiligo, bone deformity

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756 Quantification and Preference of Facial Asymmetry of the Sub-Saharan Africans' 3D Facial Models

Authors: Anas Ibrahim Yahaya, Christophe Soligo


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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755 Facial Expression Phoenix (FePh): An Annotated Sequenced Dataset for Facial and Emotion-Specified Expressions in Sign Language

Authors: Marie Alaghband, Niloofar Yousefi, Ivan Garibay


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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754 Comparing Emotion Recognition from Voice and Facial Data Using Time Invariant Features

Authors: Vesna Kirandziska, Nevena Ackovska, Ana Madevska Bogdanova


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

Procedia PDF Downloads 206
753 In vivo Mechanical Characterization of Facial Skin Combining Digital Image Correlation and Finite Element

Authors: Huixin Wei, Shibin Wang, Linan Li, Lei Zhou, Xinhao Tu


Facial skin is a biomedical material with complex mechanical properties of anisotropy, viscoelasticity, and hyperelasticity. The mechanical properties of facial skin are crucial for a number of applications including facial plastic surgery, animation, dermatology, cosmetic industry, and impact biomechanics. Skin is a complex multi-layered material which can be broadly divided into three main layers, the epidermis, the dermis, and the hypodermis. Collagen fibers account for 75% of the dry weight of dermal tissue, and it is these fibers which are responsible for the mechanical properties of skin. Many research on the anisotropic mechanical properties are mainly concentrated on in vitro, but there is a great difference between in vivo and in vitro for mechanical properties of the skin. In this study, we presented a method to measure the mechanical properties of facial skin in vivo. Digital image correlation (DIC) and indentation tests were used to obtain the experiment data, including the deformation of facial surface and indentation force-displacement curve. Then, the experiment was simulated using a finite element (FE) model. Application of Computed Tomography (CT) and reconstruction techniques obtained the real tissue geometry. A three-dimensional FE model of facial skin, including a bi-layer system, was obtained. As the epidermis is relatively thin, the epidermis and dermis were regarded as one layer and below it was hypodermis in this study. The upper layer was modeled as a Gasser-Ogden-Holzapfel (GOH) model to describe hyperelastic and anisotropic behaviors of the dermis. The under layer was modeled as a linear elastic model. In conclusion, the material properties of two-layer were determined by minimizing the error between the FE data and experimental data.

Keywords: facial skin, indentation test, finite element, digital image correlation, computed tomography

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752 Emotion Recognition with Occlusions Based on Facial Expression Reconstruction and Weber Local Descriptor

Authors: Jadisha Cornejo, Helio Pedrini


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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751 Classifying Facial Expressions Based on a Motion Local Appearance Approach

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


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

Procedia PDF Downloads 289
750 Improving the Performance of Deep Learning in Facial Emotion Recognition with Image Sharpening

Authors: Ksheeraj Sai Vepuri, Nada Attar


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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749 Somatosensory-Evoked Blink Reflex in Peripheral Facial Palsy

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


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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748 Disentangling Audio Content and Emotion with Adaptive Instance Normalization for Expressive Facial Animation Synthesis

Authors: Che-Jui Chang, Long Zhao, Mubbasir Kapadia


3D facial animation synthesis from audio has been a focus in recent years. However, most existing works in the literature are designed for the mapping between audio and visual content, providing limited knowledge regarding the relationship between emotion in audio and expressive facial animation. In this paper, we aim to generate audio-matching facial animations with the specified emotion label. In such a task, we argue that separating the content from audio is indispensable -the proposed model must learn to generate facial contents from audio contents while expressions from the specified emotion. We achieve it by an adaptive instance normalization (AdaIN) module that isolates the content in the audio and combines the emotion embedding from the specified label. The joint content-emotion embedding is then used to generate 3D facial vertices and texture maps. We compare our method with state-of-the-art baselines, including the facial segmentation-based and voice conversion-based disentanglement approaches. We also conducted a user study to evaluate the performance of emotion conditioning, and the results indicate our proposed method outperforms the baselines in both the animation quality and accuracy of expression categorization.

Keywords: adaptive instance normalization, audio-driven animation, content-emotion disentanglement, emotion-conditioning, expressive facial animation synthesis

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747 KSVD-SVM Approach for Spontaneous Facial Expression Recognition

Authors: Dawood Al Chanti, Alice Caplier


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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746 Noninvasive Evaluation of Acupuncture by Measuring Facial Temperature through Thermal Image

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


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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745 Facial Emotion Recognition Using Deep Learning

Authors: Ashutosh Mishra, Nikhil Goyal


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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744 Highly Realistic Facial Expressions of Anthropomorphic Social Agent as a Factor in Solving the 'Uncanny Valley' Problem

Authors: Daniia Nigmatullina, Vlada Kugurakova, Maxim Talanov


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

Procedia PDF Downloads 192
743 Curvelet Features with Mouth and Face Edge Ratios for Facial Expression Identification

Authors: S. Kherchaoui, A. Houacine


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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742 DBN-Based Face Recognition System Using Light Field

Authors: Bing Gu


Abstract—Most of Conventional facial recognition systems are based on image features, such as LBP, SIFT. Recently some DBN-based 2D facial recognition systems have been proposed. However, we find there are few DBN-based 3D facial recognition system and relative researches. 3D facial images include all the individual biometric information. We can use these information to build more accurate features, So we present our DBN-based face recognition system using Light Field. We can see Light Field as another presentation of 3D image, and Light Field Camera show us a way to receive a Light Field. We use the commercially available Light Field Camera to act as the collector of our face recognition system, and the system receive a state-of-art performance as convenient as conventional 2D face recognition system.

Keywords: DBN, face recognition, light field, Lytro

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741 Tick Induced Facial Nerve Paresis: A Narrative Review

Authors: Jemma Porrett


Background: We present a literature review examining the research surrounding tick paralysis resulting in facial nerve palsy. A case of an intra-aural paralysis tick bite resulting in unilateral facial nerve palsy is also discussed. Methods: A novel case of otoacariasis with associated ipsilateral facial nerve involvement is presented. Additionally, we conducted a review of the literature, and we searched the MEDLINE and EMBASE databases for relevant literature published between 1915 and 2020. Utilising the following keywords; 'Ixodes', 'Facial paralysis', 'Tick bite', and 'Australia', 18 articles were deemed relevant to this study. Results: Eighteen articles included in the review comprised a total of 48 patients. Patients' ages ranged from one year to 84 years of age. Ten studies estimated the possible duration between a tick bite and facial nerve palsy, averaging 8.9 days. Forty-one patients presented with a single tick within the external auditory canal, three had a single tick located on the temple or forehead region, three had post-auricular ticks, and one patient had a remarkable 44 ticks removed from the face, scalp, neck, back, and limbs. A complete ipsilateral facial nerve palsy was present in 45 patients, notably, in 16 patients, this occurred following tick removal. House-Brackmann classification was utilised in 7 patients; four patients with grade 4, one patient with grade three, and two patients with grade 2 facial nerve palsy. Thirty-eight patients had complete recovery of facial palsy. Thirteen studies were analysed for time to recovery, with an average time of 19 days. Six patients had partial recovery at the time of follow-up. One article reported improvement in facial nerve palsy at 24 hours, but no further follow-up was reported. One patient was lost to follow up, and one article failed to mention any resolution of facial nerve palsy. One patient died from respiratory arrest following generalized paralysis. Conclusions: Tick paralysis is a severe but preventable disease. Careful examination of the face, scalp, and external auditory canal should be conducted in patients presenting with otalgia and facial nerve palsy, particularly in tropical areas, to exclude the possibility of tick infestation.

Keywords: facial nerve palsy, tick bite, intra-aural, Australia

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740 The Effects of Affective Dimension of Face on Facial Attractiveness

Authors: Kyung-Ja Cho, Sun Jin Park


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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739 Dynamic Gabor Filter Facial Features-Based Recognition of Emotion in Video Sequences

Authors: T. Hari Prasath, P. Ithaya Rani


In the world of visual technology, recognizing emotions from the face images is a challenging task. Several related methods have not utilized the dynamic facial features effectively for high performance. This paper proposes a method for emotions recognition using dynamic facial features with high performance. Initially, local features are captured by Gabor filter with different scale and orientations in each frame for finding the position and scale of face part from different backgrounds. The Gabor features are sent to the ensemble classifier for detecting Gabor facial features. The region of dynamic features is captured from the Gabor facial features in the consecutive frames which represent the dynamic variations of facial appearances. In each region of dynamic features is normalized using Z-score normalization method which is further encoded into binary pattern features with the help of threshold values. The binary features are passed to Multi-class AdaBoost classifier algorithm with the well-trained database contain happiness, sadness, surprise, fear, anger, disgust, and neutral expressions to classify the discriminative dynamic features for emotions recognition. The developed method is deployed on the Ryerson Multimedia Research Lab and Cohn-Kanade databases and they show significant performance improvement owing to their dynamic features when compared with the existing methods.

Keywords: detecting face, Gabor filter, multi-class AdaBoost classifier, Z-score normalization

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738 ARTHUR-3D Dentofacial Surgery Full Planning

Authors: Oliveira M., Gonçalves L., Vale F., Caramelo F., Francisco I.


Facial expression facilitates the understanding of the individual's identity, being essential for communication and interaction in modern society. When this expression is limited, in addition to the functional consequences of the organism, it also has psychological and social consequences. The ARTHUR project developed a virtual surgery solution, applied to the bone and dental structure, capable of predicting the real impact on the patient's face mask. The solution is based on cloud and allows the clinical body to perform the virtual surgical planning, using cutting guides and plates or surgical guide lines, in a parameterized anatomical model of the head achieved through the fusion of three exams: TAC (CBCT), Intraoral Scan and 3D Stereo Photogrammetry. Above all, it is intended that, based on this planning and thanks to the parameterized anatomical model, it is possible to realistically forecast and represent the impact of the surgical intervention on the patient's face mask. This tool acts in different situations that require facial reconstruction, however, this project focuses specifically on two types of use cases: bone congenital disfigurement and acquired disfiguration such as oral cancer with bone attainment. It is intended to be an intuitive and user friendly tool, which allows its use by less specialized technicians who can demonstrate the final results directly to the patient in the office. Able to predict visual impact with high realism and degree trust will enable patients to participate more actively in the decision-making process therapy.

Keywords: 3D computing, image processing, image registry, image reconstruction

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737 Analysis and Detection of Facial Expressions in Autism Spectrum Disorder People Using Machine Learning

Authors: Muhammad Maisam Abbas, Salman Tariq, Usama Riaz, Muhammad Tanveer, Humaira Abdul Ghafoor


Autism Spectrum Disorder (ASD) refers to a developmental disorder that impairs an individual's communication and interaction ability. Individuals feel difficult to read facial expressions while communicating or interacting. Facial Expression Recognition (FER) is a unique method of classifying basic human expressions, i.e., happiness, fear, surprise, sadness, disgust, neutral, and anger through static and dynamic sources. This paper conducts a comprehensive comparison and proposed optimal method for a continued research project—a system that can assist people who have Autism Spectrum Disorder (ASD) in recognizing facial expressions. Comparison has been conducted on three supervised learning algorithms EigenFace, FisherFace, and LBPH. The JAFFE, CK+, and TFEID (I&II) datasets have been used to train and test the algorithms. The results were then evaluated based on variance, standard deviation, and accuracy. The experiments showed that FisherFace has the highest accuracy for all datasets and is considered the best algorithm to be implemented in our system.

Keywords: autism spectrum disorder, ASD, EigenFace, facial expression recognition, FisherFace, local binary pattern histogram, LBPH

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736 Data Collection Techniques for Robotics to Identify the Facial Expressions of Traumatic Brain Injured Patients

Authors: Chaudhary Muhammad Aqdus Ilyas, Matthias Rehm, Kamal Nasrollahi, Thomas B. Moeslund


This paper presents the investigation of data collection procedures, associated with robots when placed with traumatic brain injured (TBI) patients for rehabilitation purposes through facial expression and mood analysis. Rehabilitation after TBI is very crucial due to nature of injury and variation in recovery time. It is advantageous to analyze these emotional signals in a contactless manner, due to the non-supportive behavior of patients, limited muscle movements and increase in negative emotional expressions. This work aims at the development of framework where robots can recognize TBI emotions through facial expressions to perform rehabilitation tasks by physical, cognitive or interactive activities. The result of these studies shows that with customized data collection strategies, proposed framework identify facial and emotional expressions more accurately that can be utilized in enhancing recovery treatment and social interaction in robotic context.

Keywords: computer vision, convolution neural network- long short term memory network (CNN-LSTM), facial expression and mood recognition, multimodal (RGB-thermal) analysis, rehabilitation, robots, traumatic brain injured patients

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735 Correction of Skeletal Deformity by Surgical Approach – A Case Report

Authors: Davender Kumar, Virender Singh, Rekha Sharma


Correction of skeletal deformities in adult patients with orthodontics is limited. In adult severe cases, the combined approach, orthodontic and orthognathic surgery, is always the treatment of choice, and the results obtained usually ensure a better esthetic, functional, and stable results Orthognathic surgery is the best option for cases when camouflage treatment is questionable and growth modulation is not possible. This case report illustrates the benefit of the team approach in correcting mandible retrusion along with class II skeletal deformity with 100% deep bite. Correction was achieved by anterior repositioning of mandible osteotomy along with orthodontic treatment. The patient's facial appearance was markedly improved along with functional and stable occlusion.

Keywords: camouflage, skeletal, orthognathic, dental

Procedia PDF Downloads 319
734 Facial Expression Recognition Using Sparse Gaussian Conditional Random Field

Authors: Mohammadamin Abbasnejad


The analysis of expression and facial Action Units (AUs) detection are very important tasks in fields of computer vision and Human Computer Interaction (HCI) due to the wide range of applications in human life. Many works have been done during the past few years which has their own advantages and disadvantages. In this work, we present a new model based on Gaussian Conditional Random Field. We solve our objective problem using ADMM and we show how well the proposed model works. We train and test our work on two facial expression datasets, CK+, and RU-FACS. Experimental evaluation shows that our proposed approach outperform state of the art expression recognition.

Keywords: Gaussian Conditional Random Field, ADMM, convergence, gradient descent

Procedia PDF Downloads 240
733 When and Why Unhappy People Avoid Enjoyable Experiences

Authors: Hao Shen, Aparna Labroo


Across four studies, we show people in a negative mood avoid anticipated enjoyable experiences because of the subjective difficulty in simulating those experiences, and they misattribute these feelings of difficulty to reduced pleasantness of the anticipated experience. We observe the avoidance of enjoyable experiences only for anticipated experiences that involve smile-like facial-muscular simulation. When the need for facial-muscular simulation is attenuated, or when the anticipated experience relies on facial-muscular simulation to a lesser extent, people in a negative mood no longer avoid enjoyable experiences, but rather seek such experiences because they fit better with their ongoing mood-repair goals.

Keywords: emotion regulation, mood repair, embodiment, anticipated experiences

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732 The Incidence of Inferior Alveolar Nerve Dysfunction Following Bilateral Sagittal Split Osteotomies: A Single Centre Retrospective Audit in the United Kingdom

Authors: Krupali Mukeshkumar, Jinesh Shah


Background: Bilateral Sagittal Split Osteotomy (BSSO), used for the correction of mandibular deformities, is a common oral and maxillofacial surgical procedure. Inferior alveolar nerve dysfunction is commonly reported post-operatively by patients as paresthesia or anesthesia. The current literature lacks a consensus on the incidence of inferior alveolar nerve dysfunction as patients are not routinely assessed pre and post-operatively with an objective assessment. The range of incidence varies from 9% to 85% of patients, with some authors arguing that 100% of patients experience nerve dysfunction immediately post-surgery. Systematic reviews have shown a difference between incidence rates at different follow-up periods using objective and subjective methods. Aim: To identify the incidence of inferior alveolar nerve dysfunction following BSSO. Gold standard: Nerve dysfunction incidence rates similar or lower than current literature of 83% day one post-operatively and 18.4% at one year follow up. Setting: A retrospective cross-sectional audit of patients treated between 2017-2019 at the Royal Stoke University Hospital, Maxillofacial and Orthodontic departments. Sample: All patients who underwent a BSSO (with or without le fort one osteotomy) between 2017–2019 were identified from the database. Patients with pre-existing neurosensory disturbance, those who had a genioplasty at the same time and those with no follow-up were excluded. The sample consisted of 121 patients, 37 males and 84 females between the ages of 17-50 years at the time of surgery. Methods: Clinical records of 121 cases were reviewed to assess the age, sex, type of mandibular osteotomy, status of the nerve during the surgical procedure, type of bony split and incidence of nerve dysfunction at follow-up appointments. The surgical procedure was carried out by three Maxillo-facial surgeons and follow-up appointments were carried out in the Orthodontic and Oral and Maxillo-facial departments. Results: 120 patients were treated to correct the mandibular facial deformity and 1 patient was treated for sleep apnoea. Seventeen patients had a mandibular setback and 104 patients had mandibular advancement. 68 patients reported inferior alveolar nerve dysfunction at one week following their surgery. Seventy-six patients had temporary paresthesia present between 2 weeks and 12 months post-surgery. 13 patients had persistent nerve dysfunction at 12 months, of which 1 had a bad bony split during the BSSO. The incidence of nerve dysfunction postoperatively was 6.6% after 1 day, 56.1% at 1 week, 62.8% at 2 weeks, 59.5% between 3-6 weeks, 43.0% between 8-16 weeks and 10.7% at 1 year. Conclusions: The results of this audit show a similar incidence rate to the research gold standard at the one-year follow-up. Future Recommendations: No changes to surgical procedure or technique are indicated, but a need for improved documentation and a standardized approach for assessment of post-operative nerve dysfunction would be beneficial.

Keywords: bilateral sagittal split osteotomy, inferior alveolar nerve, mandible, nerve dysfunction

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731 A Theoretical Study on Pain Assessment through Human Facial Expresion

Authors: Mrinal Kanti Bhowmik, Debanjana Debnath Jr., Debotosh Bhattacharjee


A facial expression is undeniably the human manners. It is a significant channel for human communication and can be applied to extract emotional features accurately. People in pain often show variations in facial expressions that are readily observable to others. A core of actions is likely to occur or to increase in intensity when people are in pain. To illustrate the changes in the facial appearance, a system known as Facial Action Coding System (FACS) is pioneered by Ekman and Friesen for human observers. According to Prkachin and Solomon, a set of such actions carries the bulk of information about pain. Thus, the Prkachin and Solomon pain intensity (PSPI) metric is defined. So, it is very important to notice that facial expressions, being a behavioral source in communication media, provide an important opening into the issues of non-verbal communication in pain. People express their pain in many ways, and this pain behavior is the basis on which most inferences about pain are drawn in clinical and research settings. Hence, to understand the roles of different pain behaviors, it is essential to study the properties. For the past several years, the studies are concentrated on the properties of one specific form of pain behavior i.e. facial expression. This paper represents a comprehensive study on pain assessment that can model and estimate the intensity of pain that the patient is suffering. It also reviews the historical background of different pain assessment techniques in the context of painful expressions. Different approaches incorporate FACS from psychological views and a pain intensity score using the PSPI metric in pain estimation. This paper investigates in depth analysis of different approaches used in pain estimation and presents different observations found from each technique. It also offers a brief study on different distinguishing features of real and fake pain. Therefore, the necessity of the study lies in the emerging fields of painful face assessment in clinical settings.

Keywords: facial action coding system (FACS), pain, pain behavior, Prkachin and Solomon pain intensity (PSPI)

Procedia PDF Downloads 220
730 Gender Recognition with Deep Belief Networks

Authors: Xiaoqi Jia, Qing Zhu, Hao Zhang, Su Yang


A gender recognition system is able to tell the gender of the given person through a few of frontal facial images. An effective gender recognition approach enables to improve the performance of many other applications, including security monitoring, human-computer interaction, image or video retrieval and so on. In this paper, we present an effective method for gender classification task in frontal facial images based on deep belief networks (DBNs), which can pre-train model and improve accuracy a little bit. Our experiments have shown that the pre-training method with DBNs for gender classification task is feasible and achieves a little improvement of accuracy on FERET and CAS-PEAL-R1 facial datasets.

Keywords: gender recognition, beep belief net-works, semi-supervised learning, greedy-layer wise RBMs

Procedia PDF Downloads 332