• Journal of KIISE:Computing Practices and Letters
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• v.16 no.4
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• pp.457-461
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• 2010

Even though face recognition researches have been developed for a long ago, there is no practical face recognition system in real life. It is caused by several real situations where non-facial components such as glasses, scarf, and hair occlude facial components while facial images in a face database are well designed. This occlusion decreases recognition performance. Previous approaches in recent years have tried to solve non-facial components but have not resulted in enough performance. In this paper, we propose a method to handle this problem based on support vector data description, which trains the hyperball in feature space to find the minimum distance estimating the approximated face. In order to evaluate its performance and validate the effectiveness of the proposed method, we make several experiments and the results show that the proposed method has a considerable effectiveness.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.126-132
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• 2000

This paper presents a facial expression recognition based on Gabor wavelets that uses a fuzzy C-means(FCM) clustering algorithm and neural network. Features of facial expressions are extracted to two steps. In the first step, Gabor wavelet representation can provide edges extraction of major face components using the average value of the image's 2-D Gabor wavelet coefficient histogram. In the next step, we extract sparse features of facial expressions from the extracted edge information using FCM clustering algorithm. The result of facial expression recognition is compared with dimensional values of internal stated derived from semantic ratings of words related to emotion. The dimensional model can recognize not only six facial expressions related to Ekman's basic emotions, but also expressions of various internal states.

• Journal of KIISE:Software and Applications
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• v.27 no.7
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• pp.731-741
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• 2000

This paper proposes a method to detect a facial region and extract facial features which is crucial for visual recognition of human faces. In this paper, we extract the MER(Minimum Enclosing Rectangle) of a face and facial components using projection analysis on both edge image and binary image. We use an active contour model(snakes) for extraction of the contours of eye, mouth, eyebrow, and face in order to reflect the individual differences of facial shapes and converge quickly. The determination of initial contour is very important for the performance of snakes. Particularly, we detect Minimum Enclosing Rectangle(MER) of facial components and then determine initial contours using general shape of facial components within the boundary of the obtained MER. We obtained experimental results to show that MER extraction of the eye, mouth, and face was performed successfully. But in the case of images with bright eyebrow, MER extraction of eyebrow was performed poorly. We obtained good contour extraction with the individual differences of facial shapes. Particularly, in the eye contour extraction, we combined edges by first order derivative operator and zero crossings by second order derivative operator in designing energy function of snakes, and we achieved good eye contours. For the face contour extraction, we used both edges and grey level intensity of pixels in designing of energy function. Good face contours were extracted as well.

• Journal of the Korea Computer Graphics Society
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• v.14 no.2
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• pp.27-33
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• 2008

We propose a stylized facial illustration method that expresses important features of a target highly abstractly but effectively from a human facial picture. Our method first detects facial components such as eyes and their associated regions from an input image, and then uses the detected results to render a stylized portrait. Our illustration method mainly consists of two key components and additional components: a tonal illustration component to draw simple tones, a line illustration component to draw a set of lines, and additional illustration components for hair, clothes. etc. The illustration part of the proposed method aims at illustrating features of a target effectively in a highly abstracted way like hand-drawn paintings. In order to achieve this goal, our method adopts an oriental black-ink painting style, which expresses objects effectively with empty spaces and simple expressions such as abstracted lines.

• Journal of Korea Multimedia Society
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• v.9 no.8
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• pp.982-999
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• 2006

In this paper, we propose an automatic facial phrenology analysis and avatar drawing system based on internet using multi color information and face geometry. In the proposed system, we detect face using logical product of Cr and I which is a components of YCbCr and YIQ color model, respectively. And then, we extract facial feature using face geometry and analyze user's facial phrenology with the classification of each facial feature. And also, the proposed system can make avatar drawing automatically using extracted and classified facial features. Experimental result shows that proposed algorithm can analyze facial phrenology as well as detect and recognize user's face at real-time.

• The Journal of Korea Robotics Society
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• v.4 no.3
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• pp.192-200
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• 2009

In this paper, we report the progress in the development of performance evaluation method for detection algorithms of face region and facial components. This paper aims to provide a standardized evaluation method for general approach in face recognition application as a potential component in futuristic intelligent robot systems. From an image capture process to the retrieval of face-related information, all the necessary steps are shown with examples.

• Journal of the Korea Fashion and Costume Design Association
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• v.19 no.4
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• pp.17-27
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• 2017

This study analyzes the trends of photo image components and forms of expression in global fashion advertising photos. First, photo image components are classified into seven categories: location (indoor-outdoor), the model's movement, pose, facial expression, gender, race and number of models. The forms of expression are classified into six categories: direct expression, sensual expression, symbolic expression, storytelling expression, dramatic expression, and sexual expression. With the aforementioned classifications, the trends were studied for three years from 2013 to 2015. The analysis result indicates the following: for the details of photo image components, the portion of indoor photos, static poses and conscious facial expressions was over 60% of the total for every season of the 3 years, while there was a slight increase in the number of models and the diversity of races. For the forms of expression, the sensual expression showed the largest portion accounting for over 50% of the total, followed by direct expression and storytelling expression. The findings from this study show that the trends of photo image components and forms of expression in global fashion advertisements are changing. Therefore, domestic companies will need to develop photo image components and forms of expression in line with the changing global fashion advertisement trends.

• Korean Journal of Cognitive Science
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• v.11 no.2
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• pp.53-58
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• 2000

This paper reconstructs local region of a facial expression image from extracted feature points of facial expression image using FCM(Fuzzy C-Meang) clustering algorithm with Gabor wavelets. The feature extraction in a face is two steps. In the first step, we accomplish the edge extraction of main components of face using average value of 2-D Gabor wavelets coefficient histogram of image and in the next step, extract final feature points from the extracted edge information using FCM clustering algorithm. This study presents that the principal components of facial expression images can be reconstructed with only a few feature points extracted from FCM clustering algorithm. It can also be applied to objects recognition as well as facial expressions recognition.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.1
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• pp.39-48
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• 2005

According to traditional 2D animation techniques, anticipation makes an animation much convincing and expressive. We present an automatic method for inserting anticipation effects to an existing facial animation. Our approach assumes that an anticipatory facial expression can be found within an existing facial animation if it is long enough. Vertices of the face model are classified into a set of components using principal components analysis directly from a given hey-framed and/or motion -captured facial animation data. The vortices in a single component will have similar directions of motion in the animation. For each component, the animation is examined to find an anticipation effect for the given facial expression. One of those anticipation effects is selected as the best anticipation effect, which preserves the topology of the face model. The best anticipation effect is automatically blended with the original facial animation while preserving the continuity and the entire duration of the animation. We show experimental results for given motion-captured and key-framed facial animations. This paper deals with a part of broad subject an application of the principles of traditional 2D animation techniques to 3D animation. We show how to incorporate anticipation into 3D facial animation. Animators can produce 3D facial animation with anticipation simply by selecting the facial expression in the animation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.04a
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• pp.247-250
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• 2005

In numerous occasions, there is need to reconstruct partially occluded facial image. Typical examples include the recognition of criminals whose facial images are captured by surveillance cameras- ln such cases a significant part of the face is occluded making the process of identification extremely difficult, both for automatic face recognition systems and human observers. To overcome these difficulties, we consider the application of Kernel PCA-based denoising method to partially occluded facial image in this paper.