• 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.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.1_2
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• pp.128-136
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• 2006

The stippling techniques, which represent objects with numerous points using pen and ink. The previous stippling techniques for Non-Photorsealistc Rendering(NPR) use single-colored points to represent the tone of gray image ur the material of surface. This paper presents a new stippling technique with various colored points based on the analysis of color information. By using the color information of the input image on HSV model, we define the color weight function that allows to determine automatically the number and size of points. The color jittering based on Munsell's color model can generate stippling drawings using various colored points to represent the image. Our color stippling method is expected to be used in many areas such as animation, digital art, video processing and CG tool.

• Archives of design research
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• v.17 no.2
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• pp.55-66
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• 2004

Full-length Animation has been producing very actively with a large of U.S.A and growing rapidly as a pare of entertainment industry since the middle of the 1990's. However, in actual fact, Korea Animation doesn't have any characteristics as compared with Japan Animation & U.S.A Animation's growth. It is owing to in financial difficulty and that there's no conversion about consciousness that Animation is only for children. This study is constructed with color information as the central figure from a gradation of information delivery and analyzed ‘Image Color’ of full-length animation which is produced by large studio in U.S.A. This study predicts about past, present and future of animation centering around a color that visual sensitivity factor which recognize enormous information very quickly among sensitivity stimulus of human being. With this study analysis a color of U.S.A animation, looking for sensitivity color factor that react to elaborate and delicate stimulus, and then expressed color from developed animation skill apply to sensitivity industry.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.532-535
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• 2008

The requirement of Digital Culture Content(Movie, Music, Animation, Digital TV, Exhibition and etc.) is increasing so variety and quantity of content is also increasing. The Movie what majority of the digital Content is developing of technology and data. In the result, the efficient retrieval service has required and user want to use a recommendation engine and semantic retrieval methods through the recommendation system. Therefore, this paper will suggest analysing trait element of digital content data, building of retrieval technology, analysing and retrieval technology base on KANSEI vocabulary and etc. For the these, we made a extraction technology of trait element based on semantics and KANSEI processing algorithm based on color information.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1999.11b
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• pp.15-20
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• 1999

본 논문에서는 사람의 정면 얼굴을 찍은 컬러 동영상에서 얼굴의 각 구성 요소에 대한 특징점들을 추출하여 3차원 개인 얼굴 모델을 생성하고 이를 얼굴의 표정 움직임에 따라 애니메이션 하는 방법을 제시한다. 제안된 방법은 얼굴의 정면만을 촬영하도록 고안된 헬멧형 카메라( Head-mounted camera)를 사용하여 얻은 2차원 동영상의 첫 프레임(frame)으로부터 얼굴의 특징점들을 추출하고 이들과 3차원 일반 얼굴 모델을 바탕으로 3차원 얼굴 특징점들의 좌표를 산출한다. 표정의 변화는 초기 영상의 특징점 위치와 이 후 영상들에서의 특징점 위치의 차이를 기반으로 알아낼 수 있다. 추출된 특징점 및 얼굴 움직임은 보다 다양한 응용 이 가능하도록 최근 1단계 표준이 마무리된 MPEG-4 SNHC의 FDP(Facial Definition Parameters)와FAP(Facial Animation Parameters)의 형식으로 표현되며 이를 이용하여 개인 얼굴 모델 및 애니메이션을 수행하였다. 제안된 방법은 단일 카메라로부터 촬영되는 영상을 기반으로 이루어지는 MPEG-4 기반 화상 통신이나 화상 회의 시스템 등에 유용하게 사용될 수 있다.

• The KIPS Transactions:PartB
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• v.14B no.4
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• pp.311-320
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• 2007

This paper presents vision-based 3D facial expression animation technique and system which provide the robust 3D head pose estimation and real-time facial expression control. Many researches of 3D face animation have been done for the facial expression control itself rather than focusing on 3D head motion tracking. However, the head motion tracking is one of critical issues to be solved for developing realistic facial animation. In this research, we developed an integrated animation system that includes 3D head motion tracking and facial expression control at the same time. The proposed system consists of three major phases: face detection, 3D head motion tracking, and facial expression control. For face detection, with the non-parametric HT skin color model and template matching, we can detect the facial region efficiently from video frame. For 3D head motion tracking, we exploit the cylindrical head model that is projected to the initial head motion template. Given an initial reference template of the face image and the corresponding head motion, the cylindrical head model is created and the foil head motion is traced based on the optical flow method. For the facial expression cloning we utilize the feature-based method, The major facial feature points are detected by the geometry of information of the face with template matching and traced by optical flow. Since the locations of varying feature points are composed of head motion and facial expression information, the animation parameters which describe the variation of the facial features are acquired from geometrically transformed frontal head pose image. Finally, the facial expression cloning is done by two fitting process. The control points of the 3D model are varied applying the animation parameters to the face model, and the non-feature points around the control points are changed by use of Radial Basis Function(RBF). From the experiment, we can prove that the developed vision-based animation system can create realistic facial animation with robust head pose estimation and facial variation from input video image.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.1012-1018
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• 2007

본 논문에서는 비전 기반 3차원 얼굴 모델의 자동 표정 생성 시스템을 제안한다. 기존의 3차원 얼굴 애니메이션에 관한 연구는 얼굴의 움직임을 나타내는 모션 추정을 배제한 얼굴 표정 생성에 초점을 맞추고 있으며 얼굴 모션 추정과 표정 제어에 관한 연구는 독립적으로 이루어지고 있다. 제안하는 얼굴 모델의 표정 생성 시스템은 크게 얼굴 검출, 얼굴 모션 추정, 표정 제어로 구성되어 있다. 얼굴 검출 방법으로는 얼굴 후보 영역 검출과 얼굴 영역 검출 과정으로 구성된다. HT 컬러 모델을 이용하며 얼굴의 후보 영역을 검출하며 얼굴 후보 영역으로부터 PCA 변환과 템플릿 매칭을 통해 얼굴 영역을 검출하게 된다. 검출된 얼굴 영역으로부터 얼굴 모션 추정과 얼굴 표정 제어를 수행한다. 3차원 실린더 모델의 투영과 LK 알고리즘을 이용하여 얼굴의 모션을 추정하며 추정된 결과를 3차원 얼굴 모델에 적용한다. 또한 영상 보정을 통해 강인한 모션 추정을 할 수 있다. 얼굴 모델의 표정을 생성하기 위해 특징점 기반의 얼굴 모델 표정 생성 방법을 적용하며 12개의 얼굴 특징점으로부터 얼굴 모델의 표정을 생성한다. 얼굴의 구조적 정보와 템플릿 매칭을 이용하여 눈썹, 눈, 입 주위의 얼굴 특징점을 검출하며 LK 알고리즘을 이용하여 특징점을 추적(Tracking)한다. 추적된 특징점의 위치는 얼굴의 모션 정보와 표정 정보의 조합으로 이루어져있기 때문에 기하학적 변환을 이용하여 얼굴의 방향이 정면이었을 경우의 특징점의 변위인 애니메이션 매개변수를 획득한다. 애니메이션 매개변수로부터 얼굴 모델의 제어점을 이동시키며 주위의 정점들은 RBF 보간법을 통해 변형한다. 변형된 얼굴 모델로부터 얼굴 표정을 생성하며 모션 추정 결과를 모델에 적용함으로써 얼굴 모션 정보가 결합된 3차원 얼굴 모델의 표정을 생성한다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.5
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• pp.512-520
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• 2019

It is quite useful to represent speeches visually for learners who study foreign languages as well as the hearing impaired who cannot directly hear speeches, and a number of researches have been presented in the literature. They remain, however, at the level of representing the characteristics of speeches using colors or showing the changing shape of lips and mouth using the animation-based representation. As a result of such approaches, those methods cannot tell the users how far their pronunciations are away from the standard ones, and moreover they make it technically difficult to develop such a system in which users can correct their pronunciation in an interactive manner. In order to address these kind of drawbacks, this paper proposes a speech visualization model based on the relative distance between the user's speech and the standard one, furthermore suggests actual implementation directions by applying the proposed model to the visualization of Korean vowels. The method extract three formants F1, F2, and F3 from speech signals and feed them into the Kohonen's SOM to map the results into 2-D screen and represent each speech as a pint on the screen. We have presented a real system implemented using the open source formant analysis software on the speech of a Korean instructor and several foreign students studying Korean language, in which the user interface was built using the Javascript for the screen display.