• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.11
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• pp.1470-1481
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• 2004

The purpose of this study was to research on facial shape to suggest a quantified data for the domestic apparel and beauty industry. Conducted a measurement research of 278 female college students, We took the photographs of front view and lateral view of the subjects by digital camera and obtained the 69 measurements through the facial measurement program. 264 ,subjects' measurement data were analyzed by various statistical methods such as descriptive analysis, factor analysis and cluster analysis. Using the 69 measurement items,4 factors were selected as key factors for the factor analysis of facial shape, the factors are: \circled1 Front face height \circled2 Side face radial length \circled3 Front face breadth \circled4 Ear height and Gnathion radial length. We categorized the facial shape into four types by cluster analysis. Type 4 is the most common facial shape in female college students: \circled1 Type 1: Round face \circled2 Type 2: Oval face \circled3 Type 3: Square face \circled4 Type 4: Heart shaped face According to the facial shape analysis, facial shape of female college students are consisting of Heart shaped face(34.8%), Round face(29.2%), Square face(23.5%), oval face(12.5%).

• Fashion & Textile Research Journal
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• v.11 no.1
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• pp.103-111
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• 2009

This study is to help make-up and coordination for image-making after analysis of facial color and shape of elderly women. The data was analyzed 55-75 years old 212 elderly women's face color and pictures by means of SPSS 12.0 statistics package. On the basis of the colorimetric data on face by Minolta CM2500D, this research considered the analysis of facial color, patternization of facial color and its analysis by age group; for the analysis of facial shape, this research patternized facial shape and analyzed its characteristic using both contour-based facial shape analysis and Kamata facial shape analysis. As for facial color, it was found that the lower age bracket has bright and reddish face, looking fine, while the higher age bracket has a conspicuously yellowish face, looking bad. The community of facial color is classified as 3 types and it was found out that the facial color of the subjects belonging to Type 3, whose L value is the largest, looked the brightest; the face of the subjects belonging to Type 2, whose a value is the largest, was much tinged with red, and the face of the subjects belonging to Type 1, whose b value is the largest were tinged with yellow. According to the analysis of facial shape, there appeared oval & long forms in the classification by contour, while there appeared a lot of downward-directed power and inner-directed power in the classification by Kamata, which is believed to reflect the phenomenon that their chin line becomes roundish and the facial length also tend to be longer due to aging.

• Journal of the Korean Society of Costume
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• v.44
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• pp.104-116
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• 1999

This study was intended to make an inquiry into the effect of lines, shapes and colors (achromatic colors) as apparel design elements on the perceptions of facial size, brightness and shape through an empirical research based on the theories of visual perception and optical illusion that have been studied in Gestalt Psychology, which becomes the basis of apparel design principles. It was shown that the facial size was influenced by the collar size, the degree of neckline cut, and the thickness of the trimming line. The white scarf with the white jacket made the face look darkest while the black scarf with the black jacket made the face look brightest. When the neckline had the characteristic of the line contrasted with the facial shape, the oval-shaped face was perceived to be the most ideal. When the facial shape and the neckline shape were similar, the facial shape was perceived to be more highlighted.

• Journal of International Society for Simulation Surgery
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• v.2 no.1
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• pp.7-9
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• 2015

Purpose In the many face-related application such as head pose estimation, 3D face modeling, facial appearance manipulation, the robust and fast facial feature extraction is necessary. We present the facial feature extraction method based on shape regression and feature selection for real-time facial feature extraction. Materials and Methods The facial features are initialized by statistical shape model and then the shape of facial features are deformed iteratively according to the texture pattern which is selected on the feature pool. Results We obtain fast and robust facial feature extraction result with error less than 4% and processing time less than 12 ms. The alignment error is measured by average of ratio of pixel difference to inter-ocular distance. Conclusion The accuracy and processing time of the method is enough to apply facial feature based application and can be used on the face beautification or 3D face modeling.

• Journal of the Korean Society of Clothing and Textiles
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• v.33 no.6
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• pp.938-948
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• 2009

The purpose of this study was to offer typical facial shapes Korean women in their 20's to 50's. We used facial photographs of 600 Korean women obtained from $2003\sim2004$ Size Korea Project and we measured these photographs indirectly in this study by utilizing the Venus face2D program. Total 62 measurements on the face were measured and analyzed by statistical methods. The results were as follows. First of all, the mean of face length was 196mm, top face length was 62.3mm, middle face length was 68.9mm, bottom face length was 66.5mm, mean of forehead width was 125.1mm. As based on those average sizes, we proposed a average facial size and shape of Korean women and a average facial size and shape of 20's, 30's, 40's and 50's in this study. When examined characteristic of 20's facial shape, it was recognized that the width of forehead was wider and the width of gnathion was smaller than other age groups. In the characteristic of 30's facial shape, the ratios of facial length, top of face, middle of face and bottom of face were balanced well, as comparing with other age groups. Overall, the values of facial measurement of 30's were similar to the averages of total women. In the facial shape of 40's, mean length and width of face each were the smallest among each age group. The eye shape of 40's was more drooped than the average eye shape and the protrusion of the zygomatic bone was significantly different. In case of the facial shape of 50's, it was similar to the facial shape of 40's, but mean lengths and widths of 50's face were slightly larger than the values of 40's. The eye shape of 50's was more drooped than average group and the eye length was the smallest among all age groups.

• Journal of Fashion Business
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• v.9 no.2
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• pp.28-39
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• 2005

This chapter presents how 'optical illusion' works in applying makeup and how to differentiate the direction, location and shape at eyebrow lines in the aspect at physiognomy. For this study, employed were five types of face shape produced by Photoshop program - round, square, long, inverted triangle. and diamond. The best-matched facial shape was examined through a questionnaire research after applying the optical illusion of eyebrow lines to the five types of face shape. The results were revealed to be identical to ones presented in make-up teaching materials. In conclusion, it was found that well-matched shape and size of eyebrow could make some changes in the facial impression, changing the face shape into oval shape. The facial line can be modified and supplemented by reshaping such facial parts as the eyebrow, producing well-balanced facial shape. Consequently, make-up was proved to be one of the methods which can be used to create social and psychological effect which can make a favorable facial impression and individuality, natural impression and image making depending on different purposes, taking advantage of optical illusion effect.

• Journal of Fashion Business
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• v.12 no.1
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• pp.164-172
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• 2008

A face is the place where individuals can first give their images visually. This chapter presents how 'Visual optical illusion' works in applying makeup and how to differentiate the direction, location and shape of Lip in the aspect of physiognomy. For this study, employed were five types of face shape produced by Photoshop program. The best-matched facial shape was examined through a questionnaire research after applying the optical illusion of Lip to the five types of face shape. The results were revealed to be identical to ones presented in make-up teaching materials. In conclusion, it was found that well-matched shape and size of Lip could make some changes in the facial impression, changing the face shape into oval shape. The facial line can be modified and supplemented by reshaping such facial parts as the Lip, producing well-balanced facial shape. Consequently, make-up was proved to be one of the methods which can be used to create social and psychological effect which can make a favorable facial impression and individuality, natural impression and image making depending on different purposes, taking advantage of optical illusion effect.

• The Journal of the Korea Contents Association
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• v.22 no.8
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• pp.73-80
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• 2022

Facial expression is an important means of representing characteristics in movies and animations, and facial capture technology can support the production of facial animation for 3D characters more quickly and effectively. Blendshape techniques are the most widely used methods for producing high-quality 3D face animations, but traditional blendshape often takes a long time to produce. Therefore, the purpose of this study is to achieve results that are not far behind the effectiveness of traditional production to reduce the production period of blend shape. In this paper, in order to make a blend shape, the method of using the cross-model to convey the blend shape is compared with the traditional method of making the blend shape, and the validity of the new method is verified. This study used kit boy developed by Unreal Engine as an experiment target conducted a facial capture test using two blend shape production techniques, and compared and analyzed the facial effects linked to blend shape.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.715-717
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• 2004

This paper proposes a new reconstruction method of high-resolution facial image from a low-resolution facial image based on a recursive error back-projection of top-down machine learning. A face is represented by a linear combination of prototypes of shape and texture. With the shape and texture information about the pixels in a given low-resolution facial image, we can estimate optimal coefficients for a linear combination of prototypes of shape and those of texture by solving least square minimization. Then high-resolution facial image can be obtained by using the optimal coefficients for linear combination of the high-resolution prototypes, In addition to, a recursive error back-projection is applied to improve the accuracy of synthesized 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 one captured at a distance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3685-3700
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• 2015

To avoid influences caused by pose, illumination and facial expression variations, we propose a robust three-step algorithm based on ASM and POEM for facial landmark localization. Firstly, Model Selection Factor is utilized to achieve a pose-free initialized shape. Then, we use the global shape model of ASM to describe the whole face and the texture model POEM to adjust the position of each landmark. Thirdly, a second localization is presented to discriminatively refine the subtle shape variation for some organs and contours. Experiments are conducted in four main face datasets, and the results demonstrate that the proposed method accurately localizes facial landmarks and outperforms other state-of-the-art methods.