• Journal of Institute of Control, Robotics and Systems
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• v.16 no.10
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• pp.957-962
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• 2010

If we want to recognize the human's emotion via the facial image, first of all, we need to extract the emotional features from the facial image by using a feature extraction algorithm. And we need to classify the emotional status by using pattern classification method. The AAM (Active Appearance Model) is a well-known method that can represent a non-rigid object, such as face, facial expression. The Bayesian Network is a probability based classifier that can represent the probabilistic relationships between a set of facial features. In this paper, our approach to facial feature extraction lies in the proposed feature extraction method based on combining AAM with FACS (Facial Action Coding System) for automatically modeling and extracting the facial emotional features. To recognize the facial emotion, we use the DBNs (Dynamic Bayesian Networks) for modeling and understanding the temporal phases of facial expressions in image sequences. The result of emotion recognition can be used to rehabilitate based on biofeedback for emotional disabled.

• Journal of Acupuncture Research
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• v.36 no.4
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• pp.197-203
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• 2019

The purpose of this study was to investigate useful manual therapy techniques for peripheral facial nerve palsy and to propose guidelines to be applied for current manual therapy techniques. Several databases were searched to find manual therapies for facial palsy. These therapies included cervical, and temporomandibular joint chuna manual therapy, proprioceptive neuromuscular facilitation, neuromuscular re-education, facial exercise, and mime therapy. Both cervical, and temporomandibular joint chuna manual therapy release nerve compression, helping blood circulation and nerve conduction. Proprioceptive neuromuscular facilitation uses irradiation, bilateral activation, and eccentric facilitation to improve muscle power and symmetry. Neuromuscular re-education, as a retraining tool for facial movement patterns, enhances neuromuscular feedback. Facial exercise helps the patient continuously move and massage facial muscle themselves. Mime therapy aims to develop a conscious connection between the use of certain muscles and facial expressions. The use of facial chuna manual therapy for peripheral facial nerve palsy can stimulate the proprioceptive neuromuscular receptors in the face. Peripheral facial nerve palsy has 4 phases; progress phase, plateau phase, recovery phase, and sequelae phase. Each phase needs different treatments which include relaxation, assistance, resistance, origin-insertion extension, and nerve pathway expansion.

• The Journal of the Korea Contents Association
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• v.13 no.10
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• pp.71-81
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• 2013

Facial expressions decide an image for the individual, and the ability to interpret emotion from facial expressions is the core of human relations, hence recognizing emotion through facial expression is important enough to change attitude and decisions between individuals within social relations. Children with unstable attachment development, seniors, autistic group, ADHD children and depression group showed low performance results in facial expression recognizing ability tasks, and active interventions with such groups anticipates possibilities of prevention and therapeutic effects for psychological disabilities. The quantified figures that show detailed change in position of lips, eyes and cheeks anticipates for possible applications in diverse fields such as human sensibility ergonomics, korean culture and art contents, therapeutical and educational applications to overcome psychological disabilities and as methods of non-verbal communication in the globalizing multicultural society to overcome cultural differences.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.139-146
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• 2014

This paper proposes an efficient method for automatically distinguishing various facial expressions. To recognize the emotions from facial expressions, the facial images are obtained by digital cameras, and a number of feature points were extracted. The extracted feature points are then transformed to 49-dimensional feature vectors which are robust to scale and translational variations, and the facial emotions are recognized by statistical pattern classifiers such Naive Bayes, MLP (multi-layer perceptron), and SVM (support vector machine). Based on the experimental results with 5-fold cross validation, SVM was the best among the classifiers, whose performance was obtained by 50.8% for 6 emotion classification, and 78.0% for 3 emotions.

• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.80-88
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• 2019

With more emphasis on emotional communication with users in product design field, designers' clear and prompt grasp of user's emotion has become the core activity in product design research. To increase the flexibility applying emotion measurement in the process of product design, this study has used Facial Action Coding System (FACS) of behavioral emotion measurement method in product design evaluation. To select specimens, it has flexibly used the emotional product Image Map. Then this study has selected six product irritants inducing positive, negative and neutral emotions, and conducted FACS experiment with ordinary product users of 20 generations as the experimental subject, and analyzed users' emotional state in response to the irritants through their facial expressions. It also analyzes the advantages and disadvantages of FACS in the process of product design, such as "recording users' unconscious facial expressions" and puts forward some applicable schemes, such as "choosing a product stimulus with high user response". It is expected that this paper can be helpful to the flexibility of FACS as a method to predict user's emotion in advance at the trial stage of product design before launching them to the market.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.581-586
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• 2023

Recently a drama that features a lawyer with autism spectrum disorder has attracted a lot of attention, raising interest in the difficulties faced by people with autism spectrum disorders. If the Autism spectrum gets detected early and proper education and treatment, the prognosis can be improved, so the development of the treatment is urgently needed. Drugs currently used to treat autism spectrum often have side effects, so Digital Therapeutics that have no side effects and can be supplied in large quantities are drawing attention. In this paper, we introduce 'AEmotion', an application and a Digital Therapeutic that provides emotion and facial expression learning for toddlers with an autism spectrum disorder. This system is developed as an application for smartphones to increase interest in training autistic children and to test easily. Using machine learning, this system consists of three main stages: an 'emotion learning' step to learn emotions with facial expression cards, an 'emotion identification' step to check if the user understood emotions and facial expressions properly, and an 'expression training' step to make appropriate facial expressions. Through this system, it is expected that it will help autistic toddlers who have difficulties with social interactions by having problems recognizing facial expressions and emotions.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.113-115
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• 2005

This thesis presents a method for 3D modeling of facial expression from frontal and mirror-reflected multi-image. Since the proposed system uses only one camera, two mirrors, and simple mirror's property, it is robust, accurate and inexpensive. In addition, we can avoid the problem of synchronization between data among different cameras. Mirrors located near one's cheeks can reflect the side views of markers on one's face. To optimize our system, we must select feature points of face intimately associated with human's emotions. Therefore we refer to the FDP (Facial Definition Parameters) and FAP (Facial Animation Parameters) defined by MPEG-4 SNHC (Synlhetic/Natural Hybrid Coding). We put colorful dot markers on selected feature points of face to detect movement of facial deformation when subject makes variety expressions. Before computing the 3D coordinates of extracted facial feature points, we properly grouped these points according to relative part. This makes our matching process automatically. We experiment on about twenty koreans the subject of our experiment in their late twenties and early thirties. Finally, we verify the performance of the proposed method tv simulating an animation of 3D facial expression.

• Journal of KIISE:Software and Applications
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• v.27 no.8
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• pp.827-833
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• 2000

Facial expression is an effective tool to express human emotion. In this paper, a facial expression analysis method based on the base faces and their blending ratio is proposed. The seven base faces were chosen as axes describing and analyzing arbitrary facial expression. We set up seven facial expressions such as, surprise, fear, anger, disgust, happiness, sadness, and expressionless as base faces. Facial expression was built by fitting generic 3D facial model to facial image. Two comparable methods, Genetic Algorithms and Simulated Annealing were used to search the blending ratio of base faces. The usefulness of the proposed method for facial expression analysis was proved by the facial expression synthesis results.

• The KIPS Transactions:PartA
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• v.11A no.4
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• pp.277-284
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• 2004

This paper presents a facial expression control method of 3D avatar that enables the user to select a sequence of facial frames from the facial expression space, whose level of details the user can select hierarchically. Our system creates the facial expression spare from about 2,400 captured facial frames. But because there are too many facial expressions to select from, the user faces difficulty in navigating the space. So, we visualize the space hierarchically. To partition the space into a hierarchy of subspaces, we use fuzzy clustering. In the beginning, the system creates about 11 clusters from the space of 2,400 facial expressions. The cluster centers are displayed on 2D screen and are used as candidate key frames for key frame animation. When the user zooms in (zoom is discrete), it means that the user wants to see mort details. So, the system creates more clusters for the new level of zoom-in. Every time the level of zoom-in increases, the system doubles the number of clusters. The user selects new key frames along the navigation path of the previous level. At the maximum zoom-in, the user completes facial expression control specification. At the maximum, the user can go back to previous level by zooming out, and update the navigation path. We let users use the system to control facial expression of 3D avatar, and evaluate the system based on the results.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.17 no.3
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• pp.233-240
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• 2013

Objectives The objective and universal grading system for the facial nerve palsy is needed to the objectification of treatment in Oriental medicine. In this study, the facial nerve palsy grading was developed with combination of image processing technique and Nottingham scale. Methods The developed system is composed of measurement part, image processing part, facial nerve palsy evaluation part, and display part. With the video data recorded by webcam at measurement part, the positions of marker were measured at image processing part. In evaluation part, Nottingham scales were calculated in four different facial expressions with measured marker position. The video of facial movement, time history of marker position, and Nottingham scale were displayed in display part. Results & Conclusion The developed system was applied to a normal subject and a abnormal subject with facial nerve palsy. The left-right difference of Nottingham scores was large in the abnormal compared with the normal. In normal case, the change of the length between supraorbital point and infraorbital point was larger than that of the length between lateral canthus and angle of mouth. The abnormal case showed an opposite result. The developed system showed the possibilities of the objective and universal grading system for the facial nerve palsy.