• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.711-718
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• 2003

In this paper, we propose a robust face tracking algorithm. It is based on Condensation algorithm [7] and uses skin color and facial shape as the observation measure. It is hard to integrate color weight and shape weight. So we propose the method that has two separate trackers which uses skin color and facial shape as the observation measure respectively. One tracker tracks skin colored region and the other tracks facial shape. We used importance sampling technique to limit sampling region of two trackers. For skin-colored region tracker, we propose an adaptive color model to avoid the effect of illumination change. The proposed face tracker performs robustly in clutter background and in the illumination changes.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.1
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• pp.43-50
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• 2016

This paper introduces an appearance-based facial expression recognition method using ASM landmarks which is used to acquire a detailed face region. In particular, EHMM-based algorithm and SVM classifier with histogram feature are employed to appearance-based facial expression recognition, and performance evaluation of proposed method was performed with CK and JAFFE facial expression database. In addition, performance comparison was achieved through comparison with distance-based face normalization method and a geometric feature-based facial expression approach which employed geometrical features of ASM landmarks and SVM algorithm. As a result, the proposed method using ASM-based face normalization showed performance improvements of 6.39% and 7.98% compared to previous distance-based face normalization method for CK database and JAFFE database, respectively. Also, the proposed method showed higher performance compared to geometric feature-based facial expression approach, and we confirmed an effectiveness of proposed method.

• Journal of Physiology & Pathology in Korean Medicine
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• v.22 no.5
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• pp.1057-1061
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• 2008

For the purpose of investigating the reasonable logics contained in physiognomy of east and old western medicine. hypothetical researches based on hydromechanics theory were performed concerning facial types of form and pathologic features, especially 4 types of Dr. Jisan-Essence, Qi energy. Emotional Activity and Blood(EQAB). In order to infer the functional relation between facial type forming and EQAB factors, EQAB were supposed as fluid grounded on their continual flowing or periodical change and pressure effect from its congestion. and a premise that there's a linear corresponding relationship between the appearance of organ and its physical conditions of its inner vessels is formed too. Through this work, the unit fluid model(UFM) of Essence can be assumed as circle shape formed by the high viscosity and surface tension, the UFM model of Qi energy as quadrangular shape by the scattering features to outer four directions, and the UFM of emotional activity as inverted triangular shape by the flippant and uprising features, and the UFM of blood as ellipsoid triangle by the heavy and descending features in spite of circulation. The shapes made from each UFM are reproduced in the process of human development and manifest respective facial shape through the self-reproduction method like fractal theory in the last. Conclusively. it is said that the facial form analysis method like EQAB type theory can be the useful methodology to understand the human pathological and physiological features in view of hydromechanics.

• Journal of the Korean Society of Costume
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• v.64 no.4
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• pp.1-20
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• 2014

The purpose of this study is to suppose makeup design based on formative elements of facial image according to the facial image type of Korean women in their 20s. For this study, literature review were performed. Surveys were conducted twice for empirical research. The survey targeted 220 university students in their 20s. SPSS 12.0 statistics program was used to analyze the results, and T-test, ANOVA, Scheff$\acute{e}$ test. The results of the study are as follows. First, it was concluded that the effective structural formative elements are different according to the types of facial image. Second, by analyzing the differences in perceiving naked facial image and modified face shape image, modified skin color image, modified makeup color image of all types of facial image, it was found that the formative elements are different according to facial images, and that there are differences in the effectiveness of each factors.

• 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.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.69-72
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• 2002

Human face detection has many applications such as face recognition, face or facial feature tracking, pose estimation, and expression recognition. We present a new method for automatically segmentation and face detection in color images. Skin color alone is usually not sufficient to detect face, so we combine the color segmentation and shape analysis. The algorithm consists of two stages. First, skin color regions are segmented based on the chrominance component of the input image. Then regions with elliptical shape are selected as face hypotheses. They are certificated to searching for the facial features in their interior, Experimental results demonstrate successful detection over a wide variety of facial variations in scale, rotation, pose, lighting conditions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.8
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• pp.1827-1835
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• 2010

In this paper, facial feature areas in user picture are created by facial feature points extracted by ASM(Active Shape Model). In a existing virtual make-up application, users manually select a few features that are exactly. Users are uncomfortable with this method. We propose a virtual makeup application using ASM that does not require user input. In order to express a natural makeup, the modified alpha blendings for each cosmetic are used to blend skin color with cosmetic color. The Virtual makeup application was implemented to apply Foundation, Blush, Lip Stick, Lip Liner, Eye Pencil, Eye Liner and Eye Shadow.

• The Research Journal of the Costume Culture
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• v.21 no.4
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• pp.596-605
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• 2013

The purpose of this study is to classify and recreate the grooming styles of facial hair sported by noblemen during the Joseon Dynasty. Using existent portraits painted during this period as corroborative materials, this study has identified the traditional grooming styles of facial hair sought by noblemen in this age. This study has utilized 30 facial hair styles found in the portraits of noblemen inherited from the Joseon Dynasty, which take up the majority of the portraits currently remaining in Korea. To recreate grooming styles of facial hair, this study has divided facial hair into three types according to its location: beards, moustaches and whiskers. Based on the analysis of these divided grooming styles, this study has recreated grooming styles of facial hair by using artificial modelling heads, artificial hair, artificial glue, scissors, and a comb. The grooming styles of facial hair recreated by this study are closest to those that noblemen sought and did wear during the Joseon Dynasty. The results of this study are as follows. First, they groomed their moustaches in the 八 shape. Next, they wore their beards in the shape of an inverted triangle. Finally, they also grew and groomed whiskers. Though there are individual differences in the location, length, and volume of facial hair, noblemen in the Joseon Dynasty generally sought to wear their facial hair neat and long. Little research has been done to recreate and present noblemen's grooming styles of facial hair focusing on portraits. Thus, the findings of this study are expected to be utilized as basic materials for the education and research of grooming styles of facial hair according to ages. They can also be used as basic materials for recreating facial hair in historical dramas.

• Journal of KIISE:Software and Applications
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• v.34 no.3
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• pp.266-274
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• 2007

This paper proposes a new reconstruction method of high-resolution facial image from a low-resolution facial image based on top-down machine learning and recursive error back-projection. A face is represented by a linear combination of prototypes of shape and that of texture. With the shape and texture information of each pixel in a given low-resolution facial image, we can estimate optimal coefficients for a linear combination of prototypes of shape and those that of texture by solving least square minimizations. Then high-resolution facial image can be obtained by using the optimal coefficients for linear combination of the high-resolution prototypes. In addition, a recursive error back-projection procedure is applied to improve the reconstruction accuracy of high-resolution facial image. The encouraging results of the proposed method show that our method can be used to improve the performance of the face recognition by applying our method to reconstruct high-resolution facial images from low-resolution images captured at a distance.

• 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.