• Journal of Internet Computing and Services
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• v.6 no.1
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• pp.85-93
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• 2005

This paper describes how to distribute high multi-dimensional facial expression data of vast quantity over a suitable space and produce facial expression animations by selecting expressions while animator navigates this space in real-time. We have constructed facial spaces by using about 2400 facial expression frames on this paper. These facial spaces are created by calculating of the shortest distance between two random expressions. The distance between two points In the space of expression, which is manifold space, is described approximately as following; When the linear distance of them is shorter than a decided value, if the two expressions are adjacent after defining the expression state vector of facial status using distance matrix expressing distance between two markers, this will be considered as the shortest distance (manifold distance) of the two expressions. Once the distance of those adjacent expressions was decided, We have taken a Floyd algorithm connecting these adjacent distances to yield the shortest distance of the two expressions. We have used CCA(Curvilinear Component Analysis) technique to visualize multi-dimensional spaces, the form of expressing space, into two dimensions. While the animators navigate this two dimensional spaces, they produce a facial animation by using user interface in real-time.

• Proceedings of the Korea Contents Association Conference
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• 2005.05a
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• pp.229-236
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• 2005

This paper is study about emotional Interactive avatar in cellular phone. When user ask what he want to the avatar, it answer with facial expression based on animation Charac- ter. So the user can approach more friendly to the avatar.

• Journal of Korea Game Society
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• v.10 no.5
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• pp.103-113
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• 2010

In this paper, we present a practical method for generating facial animation by using an optical motion capture system. In our setup, we assumed a situation of capturing the body motion and the facial expression simultaneously, which degrades the quality of the captured marker data. To overcome this problem, we provide an integrated framework based on the local coordinate system of each marker for labeling the marker data, hole-filling and removing noises. We justify the method by applying it to generate a short animated film.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.2
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• pp.131-136
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• 2004

According to development of media, various information is recorded in media, expression is one during interesting information. Because expression includes of relationship of human inside. Intention of inside is expressed by gesture, but expression has more information. And, expression can manufacture voluntarily, include plan of inside on the man. Also, expression has unique character in a person, have alliance that do division possibility. In this paper, to analyze expression of USB camera animation, wish to detect facial building block. Because characteristic point by person's expression change exists on face component. For component detection, in animation one frame with Capture, grasp facial position, and separate face area, and detect characteristic points of face component.

• Cartoon and Animation Studies
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• s.37
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• pp.221-245
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• 2014

With the success of the world's first 3D computer animated film, "Toy Story" in 1995, industrial development of 3D computer animation gained considerable momentum. Consequently, various 3D animations for TV were produced; in addition, high quality 3D computer animation games became common. To save a large amount of 3D animation production time and cost, technological development has been conducted actively, in accordance with the expansion of industrial demand in this field. Further, compared with the traditional approach of producing animations through hand-drawings, the efficiency of producing 3D computer animations is infinitely greater. In this study, an experiment and a comparative analysis of markerless motion capture systems for facial expression animation has been conducted that aims to improve the efficiency of 3D computer animation production. Faceware system, which is a product of Image Metrics, provides sophisticated production tools despite the complexity of motion capture recognition and application process. Faceshift system, which is a product of same-named Faceshift, though relatively less sophisticated, provides applications for rapid real-time motion recognition. It is hoped that the results of the comparative analysis presented in this paper become baseline data for selecting the appropriate motion capture and key frame animation method for the most efficient production of facial expression animation in accordance with production time and cost, and the degree of sophistication and media in use, when creating animation.

• The Journal of the Korea Contents Association
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• v.10 no.5
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• pp.90-98
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• 2010

This paper describes methodology which enables user in order to generate facial expression animation of caricature which applies a facial motion data in the vector based caricature. This method which sees was embodied with the plug-in of illustrator. And It is equipping the user interface of separate way. The data which is used in experiment attaches 28 small-sized markers in important muscular part of the actor face and captured the multiple many expression which is various with Facial Tracker. The caricature was produced in the bezier curve form which has a respectively control point from location of the important marker which attaches in the face of the actor when motion capturing to connection with motion data and the region which is identical. The facial motion data compares in the caricature and the spatial scale went through a motion calibration process too because of size. And with the user letting the control did possibly at any time. In order connecting the caricature and the markers also, we did possibly with the click the corresponding region of the caricature, after the user selects each name of the face region from the menu. Finally, this paper used a user interface of illustrator and in order for the caricature facial expression animation generation which applies a facial motion data in the vector based caricature to be possible.

• Journal of Korea Multimedia Society
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• v.12 no.8
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• pp.1128-1141
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• 2009

Graphical expressions are continuously improving, spurred by the astonishing growth of the game technology industry. Despite such improvements, users are still demanding a more natural gaming environment and true reflections of human emotions. In real life, people can read a person's moods from facial color and expression. Hence, interactive facial colors in game characters provide a deeper level of reality. In this paper we propose a facial color adaptive technique, which is a combination of an emotional model based on human emotion theory, emotional expression pattern using colors of animation contents, and emotional reaction speed function based on human personality theory, as opposed to past methods that expressed emotion through blood flow, pulse, or skin temperature. Experiments show this of expression of the Facial Color Model based on facial color adoptive technique and expression of the animation contents is effective in conveying character emotions. Moreover, the proposed Facial Color Adaptive Technique can be applied not only to 2D games, but to 3D games as well.

• Journal of the Korea Computer Graphics Society
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• v.18 no.3
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• pp.9-16
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• 2012

In this paper, we present a new method for reconstructing detailed facial expression from roughly captured data with a small number of markers. Because of the difference in the required capture resolution between the full-body capture and the facial expression capture, they hardly have been performed simultaneously. However, for generating natural animation, a simultaneous capture for body and face is essential. For this purpose, we provide a method for capturing the detailed facial expression only with a small number of markers. Our basic idea is to build a database for the facial expressions and apply the principal component analysis for reducing the dimensionality. The dimensionality reduction enables us to estimate the full data from a part of the data. We justify our method by applying it to dynamic scenes to show the viability of the method.

• Journal of the Korea Computer Graphics Society
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• v.18 no.1
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• pp.23-28
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• 2012

In this paper, we present a new method for automatically synchronize captured facial expression data with its corresponding motion data. In a usual optical motion capture set-up, a detailed facial expression can not be captured simultaneously in the motion capture session because its resolution requirement is higher than that of the motion capture. Therefore, those are captured in two separate sessions and need to be synchronized in the post-process to be used for generating a convincing character animation. Based on the patterns of the actor's neck movement extracted from those two data, we present a non-linear time warping method for the automatic synchronization. We justify our method with the actual examples to show the viability of the method.

• Journal of Internet Computing and Services
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• v.7 no.2
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• pp.23-35
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• 2006

This work presents o novel method which extract facial region und features from motion picture automatically and controls the 3D facial expression in real time. To txtract facial region and facial feature points from each color frame of motion pictures a new nonparametric skin color model is proposed rather than using parametric skin color model. Conventionally used parametric skin color models, which presents facial distribution as gaussian-type, have lack of robustness for varying lighting conditions. Thus it needs additional work to extract exact facial region from face images. To resolve the limitation of current skin color model, we exploit the Hue-Tint chrominance components and represent the skin chrominance distribution as a linear function, which can reduce error for detecting facial region. Moreover, the minimal facial feature positions detected by the proposed skin model are adjusted by using edge information of the detected facial region along with the proportions of the face. To produce the realistic facial expression, we adopt Water's linear muscle model and apply the extended version of Water's muscles to variation of the facial features of the 3D face. The experiments show that the proposed approach efficiently detects facial feature points and naturally controls the facial expression of the 3D face model.