• The KIPS Transactions:PartA
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• v.11A no.2
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• pp.189-194
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• 2004

This paper describes method to distribute much high-dimensional facial expression motion data to 2 dimensional space, and method to create facial expression animation by select expressions that want by realtime as animator navigates this space. In this paper composed expression space using about 2400 facial expression frames. The creation of facial space is ended by decision of shortest distance between any two expressions. The expression space as manifold space expresses approximately distance between two points as following. After define expression state vector that express state of each expression using distance matrix which represent distance between any markers, if two expression adjoin, regard this as approximate about shortest distance between two expressions. So, if adjacency distance is decided between adjacency expressions, connect these adjacency distances and yield shortest distance between any two expression states, use Floyd algorithm for this. To materialize expression space that is high-dimensional space, project on 2 dimensions using Sammon's Mapping. Facial animation create by realtime with animators navigating 2 dimensional space using user interface.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.25-28
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• 2002

This paper introduce a personalized facial expression recognition system. Many previous works on facial expression recognition system focus on the formal six universal facial expressions. However, it is very difficult to make such expressions for normal person without much effort and training. And in these days, the personalized service is also mainly focused by many researchers in various fields. Thus, we Propose a novel facial expression recognition system with fuzzy neural networks and robust image processing.

• Archives of Plastic Surgery
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• v.42 no.4
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• pp.461-468
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• 2015

Background Functional restoration of the facial expression is necessary after facial nerve resection to treat head and neck tumors. This study was conducted to evaluate the functional outcomes of patients who underwent facial nerve cable grafting immediately after tumor resection. Methods Patients who underwent cable grafting from April 2007 to August 2011 were reviewed, in which a harvested branch of the sural nerve was grafted onto each facial nerve division. Twelve patients underwent facial nerve cable grafting after radical parotidectomy, total parotidectomy, or schwannoma resection, and the functional facial expression of each patient was evaluated using the Facial Nerve Grading Scale 2.0. The results were analyzed according to patient age, follow-up duration, and the use of postoperative radiation therapy. Results Among the 12 patients who were evaluated, the mean follow-up duration was 21.8 months, the mean age at the time of surgery was 42.8 years, and the mean facial expression score was 14.6 points, indicating moderate dysfunction. Facial expression scores were not influenced by age at the time of surgery, follow-up duration, or the use of postoperative radiation therapy. Conclusions The results of this study indicate that facial nerve cable grafting using the sural nerve can restore facial expression. Although patients were provided with appropriate treatment, the survival rate for salivary gland cancer was poor. We conclude that immediate facial nerve reconstruction is a worthwhile procedure that improves quality of life by allowing the recovery of facial expression, even in patients who are older or may require radiation therapy.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.2
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• pp.130-137
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• 2006

In this paper, we propose a method of selecting new types of rectangle features that are suitable for facial expression recognition. The basic concept in this paper is similar to Viola's approach, which is used for face detection. Instead of previous Haar-like features we choose rectangle features for facial expression recognition among all possible rectangle types in a 3${\times}$3 matrix form using the AdaBoost algorithm. The facial expression recognition system constituted with the proposed rectangle features is also compared to that with previous rectangle features with regard to its capacity. The simulation and experimental results show that the proposed approach has better performance in facial expression recognition.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.2
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• pp.51-55
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• 2015

This paper proposes an algorithm for risk situation recognition using facial expression. The proposed method recognitions the surprise and fear expression among human's various emotional expression for recognizing dangerous situation. The proposed method firstly extracts the facial region using Harr-like technique from input, detects eye region and lip region from the extracted face. And then, the method applies Uniform LBP to each region, detects facial expression, and recognizes dangerous situation. The proposed method is evaluated for MUCT database image and web cam input. The proposed method produces good results of facial expression and discriminates dangerous situation well and the average recognition rate is 91.05%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.523-528
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• 2015

This paper proposes an algorithm for risk situation recognition using facial expression. The proposed method recognitions the surprise and fear expression among human's various emotional expression for recognizing risk situation. The proposed method firstly extracts the facial region from input, detects eye region and lip region from the extracted face. And then, the method applies Uniform LBP to each region, discriminates facial expression, and recognizes risk situation. The proposed method is evaluated for Cohn-Kanade database image to recognize facial expression. The DB has 6 kinds of facial expressions of human being that are basic facial expressions such as smile, sadness, surprise, anger, disgust, and fear expression. The proposed method produces good results of facial expression and discriminates risk situation well.

• Journal of the Semiconductor & Display Technology
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• v.16 no.4
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• pp.79-85
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• 2017

Understanding of human emotion has a high importance in interaction between human and machine communications systems. The most expressive and valuable way to extract and recognize the human's emotion is by facial expression analysis. This paper presents and implements an automatic extraction and recognition scheme of facial expression and emotion through still image. This method has three main steps to recognize the facial emotion: (1) Detection of facial areas with skin-color method and feature maps, (2) Creation of the Bezier curve on eyemap and mouthmap, and (3) Classification and distinguish the emotion of characteristic with Hausdorff distance. To estimate the performance of the implemented system, we evaluate a success-ratio with emotional face image database, which is commonly used in the field of facial analysis. The experimental result shows average 76.1% of success to classify and distinguish the facial expression and emotion.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.2
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• pp.92-99
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• 2014

This paper proposes the method of facial expression recognition based on decision tree structure. In the image of facial expression, ASM(Active Shape Model) and LBP(Local Binary Pattern) make the local features of a facial expressions extracted. The discriminant features gotten from local features make the two facial expressions of all combination classified. Through the sum of true related to classification, the combination of facial expression and local region are decided. The integration of branch classifications generates decision tree. The facial expression recognition based on decision tree shows better recognition performance than the method which doesn't use that.

• The KIPS Transactions:PartB
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• v.15B no.5
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• pp.477-486
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• 2008

Facial expression, which changes face geometry, usually has an adverse effect on the performance of a face recognition system. To improve the face recognition rate, we propose a normalization method of facial expression to diminish the difference of facial expression between probe and gallery faces. Two approaches are used to facial expression modeling and normalization from single still images using a generic facial muscle model without the need of large image databases. The first approach estimates the geometry parameters of linear muscle models to obtain a biologically inspired model of the facial expression which may be changed intuitively afterwards. The second approach uses RBF(Radial Basis Function) based interpolation and warping to normalize the facial muscle model as unexpressed face according to the given expression. As a preprocessing stage for face recognition, these approach could achieve significantly higher recognition rates than in the un-normalized case based on the eigenface approach, local binary patterns and a grey-scale correlation measure.

• Journal of Families and Better Life
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• v.32 no.5
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• pp.107-123
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• 2014

The purpose of this study is to investigate the opinions of teachers, directors, and parents about childcare teachers' facial expression language. We performed in-depth interviews based on literature and previous studies, which consisted of ten childcare teachers, ten directors, and ten parents. From the in-depth interviews, we are able to mainly conclude that all groups think that a childcare teacher's facial expression language is very important, and strongly influences interpersonal problems and work performance. Mostly, childcare teachers aim to have pleasant facial expressions. However they complain that in some situations it is difficult to do so, which causes severe stress. They argued that the facial expressions of both the director of the childcare center and the parents are also very important for children. However, the directors thought that teachers' facial expressions affect children and their parents' impressions of the teachers and quality of childcare. The parents are usually highly satisfied with the childcare when the teacher has a pleasant facial expression, which motivates the parents to have a positive impression of the teacher. Taken together, childcare teachers' facial expression language is critical for children and the childcare environment. Thus, developing an education program for facial expression language would be helpful for improving the quality of child care. Plus, childcare environments should be developed so that teachers do not experience difficulty in having pleasant facial expressions. This result might have the limitation of being collected from only female childcare teachers, directors, and parents.