• Journal of the Korea Computer Graphics Society
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• v.15 no.1
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• pp.7-15
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• 2009

In this paper, a novel framework that synthesizes and clones facial expression in parameter spaces is presented. To overcome the difficulties in manipulating face geometry models with high degrees of freedom, many parameterization methods have been introduced. In this paper, a data-driven parameterization method is proposed that represents a variety of expressions with a small set of fundamental independent movements based on the ICA technique. The face deformation due to the parameters is also learned from the data to capture the nonlinearity of facial movements. With this parameterization, one can control the expression of an animated character's face by the parameters. By separating the parameterization and the deformation learning process, we believe that we can adopt this framework for a variety applications including expression synthesis and cloning. The experimental result demonstrates the efficient production of realistic expressions using the proposed method.

• Korean Journal of Cognitive Science
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• v.11 no.2
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• pp.1-10
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• 2000

Realistic facial animation research field which communicates with human and computer using face has increased recently. The human face is the part of the body we use to recognize individuals and the important communication channel that understand the inner states like emotion. To provide the intelligent interface. computer facial animation looks like human in talking and expressing himself. Facial modeling and animation research is focused on realistic facial animation recently. In this article, we suggest the method of facial modeling and animation for realistic facial synthesis. We can make a 3D facial model for arbitrary face by using generic facial model. For more correct and real face, we make the Korean Generic Facial Model. We can also manipulate facial synthesis based on the physical characteristics of real facial muscle and skin. Many application will be developed such as teleconferencing, education, movies etc.

• Proceedings of the Korea Contents Association Conference
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• 2018.05a
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• pp.49-50
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• 2018

본 논문은 깊이 이미지 이용한 페이셜 애니메이션 제작 방법을 소개한다. iPhone X의 true depth카메라를 사용하여 사람 얼굴의 심도를 정확하게 파악하고, 균등하게 분산된 도트를 통해 얼굴의 모든 표정변화를 모바일 데이터로 기록하여, 페이셜 애니메이션을 제작하는 제작한다. 본문에서의 방식은, 기존 페이셜 애니메이션 제작 과정에서의 rigging 부분을 생략하여, 기록된 얼굴 표정 데이터를 3D 모델링에 바로 전달할 수 있다. 이런 방식을 통해 전체 페이셜 애니메이션 제작 과정을 단축시켜, 제작 방법을 더욱 간단하고 효율적이게 하였다.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.12
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• pp.726-734
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• 2004

This paper presents a facial animation method that enables the user to select a sequence of facial frames from the facial expression space, whose level of details the user can select hierarchically Our system creates the facial expression space from about 2400 captured facial frames. To represent the state of each expression, we use the distance matrix that represents the distance between pairs of feature points on the face. The shortest trajectories are found by dynamic programming. The space of facial expressions is multidimensional. To navigate this space, we visualize the space of expressions in 2D space by using the multidimensional scaling(MDS). But because there are too many facial expressions to select from, the user faces difficulty in navigating the space. So, we visualize the space hierarchically. To partition the space into a hierarchy of subspaces, we use fuzzy clustering. In the beginning, the system creates about 10 clusters from the space of 2400 facial expressions. Every tine the level increases, the system doubles the number of clusters. The cluster centers are displayed on 2D screen and are used as candidate key frames for key frame animation. The user selects new key frames along the navigation path of the previous level. At the maximum level, the user completes key frame specification. We let animators use the system to create example animations, and evaluate the system based on the results.

• 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.9 no.7
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• pp.159-170
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• 2009

It is very important to extract the expression data and capture a face image from a video for online-based 3D face animation. In recently, there are many researches on vision-based approach that captures the expression of an actor in a video and applies them to 3D face model. In this paper, we propose an automatic data extraction system, which extracts and traces a face and expression data from realtime video inputs. The procedures of our system consist of three steps: face detection, face feature extraction, and face tracing. In face detection, we detect skin pixels using YCbCr skin color model and verifies the face area using Haar-based classifier. We use the brightness and color information for extracting the eyes and lips data related facial expression. We extract 10 feature points from eyes and lips area considering FAP defined in MPEG-4. Then, we trace the displacement of the extracted features from continuous frames using color probabilistic distribution model. The experiments showed that our system could trace the expression data to about 8fps.

• 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.715-718
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• 2006

아바타를 이용한 얼굴 애니메이션은 가상 현실이나 엔터테인먼트와 같은 분야에서 많이 적용된다. 얼굴 애니메이션을 생성하는 방법에는 크게 3 차원 모델을 직접 변형시키는 기하학적인 변형 방법과 2 차원 이미지의 워핑이나 모핑방법을 이용한 이미지 변형 방법이 있다. 기하학적인 변형 방법 중 3 차원 모델을 변형시키기 위한 방법으로 RBF(Radial Basis Function)을 이용하는 방법이 있다. RBF 함수를 이용하여 모델의 부드러운 변형을 만들 수 있다. 이 방법은 모델의 임의의 한 점을 이동하게 되면 영향을 받는 정점들을 좀 더 자연스럽게 이동시킴으로써 자연스러운 애니메이션을 생성할 수 있다. 본 연구에서는 RBF 를 이용하여 3 차원 얼굴 메쉬 모델의 기하학적 변형을 통해 모델의 얼굴 표정을 생성하는 방법에 대해 제안하고자 한다. 얼굴 모델 변형을 위해 얼굴의 특징인 눈, 입, 턱 부분에 특징점을 정하고 각 특징점에 따라 영향을 받는 영역을 정하기 위해 얼굴 모델을 지역적으로 클러스터링한다. 각 특징점에 따라 영향을 받는 영역에 대해 클러스터링을 적용하고 RBF 를 이용하여 자연스러운 얼굴 표정을 생성하는 방법을 제안한다.

• Proceedings of the Korea Multimedia Society Conference
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• 2004.05a
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• pp.679-683
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• 2004

흔히 애니메이션은 캐릭터의 표정이 얼굴에만 나타난다고 생각한다. 하지만 캐릭터의 몸도 얼굴만큼이나 풍부하게 감정을 표현할 수 있다. 이에 따라 본 논문에는 캐릭터 움직임에 따른 동작이 어떻게 변화되고, 생동감 있게 움직일 것인가에 대해 알아보고자 한다. 애니메이션의 기본 동작원리에는 스쿼시, 스트레치, 동작의 속도와 타이밍, 관성, 선행동작, 포물선 따라 움직이기, 인비트위닝 등 많은 것이 있다. 이들 기본동작들은 모두 애니메이션 성공에 크게 영향을 끼친다. 애니메이션에서 캐릭터의 연기는 보는 사람들로 하여금 필요한 동작을 통하여 어떤 표현을 전달할 수 있도록 올바른 타이밍을 가져야한다. 본 논문은 애니메이션 동작을 표현하기 위해 각각의 이미지들의 표현방법에서 감성위주의 느낌들을 어떻게 보여줘야 할 것인가에 대해 다양한 표현들로 나타내었다.

• Journal of the Korea Computer Graphics Society
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• v.13 no.3
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• pp.11-18
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• 2007

Creating stylistic facial animation is one of the most important problems in character animation. Traditionally facial animation is created manually by animators of captured using motion capture systems. But this process is very difficult and labor-intensive. In this work, we present an intuitive, easy-to-use, sketch-based user interface system that facilitates the process of creating facial animation and key-frame interpolation method using facial capture data. The user of our system is allowed to create expressive speech facial animation easily and rapidly.