• Journal of Digital Contents Society
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• v.9 no.2
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• pp.331-339
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• 2008

This paper presents the development of certain highly efficient and accurate system for producing animation key data for 3D lip-synch animation. The system developed herein extracts korean phonemes from sound and text data automatically and then computes animation key data using the segmented phonemes. This animation key data is used for 3D lip-synch animation system developed herein as well as commercial 3D facial animation system. The conventional 3D lip-synch animation system segments the sound data into the phonemes based on English phonemic system and produces the lip-synch animation key data using the segmented phoneme. A drawback to this method is that it produces the unnatural animation for Korean contents. Another problem is that this method needs the manual supplementary work. In this paper, we propose the 3D lip-synch animation system that can segment the sound and text data into the phonemes automatically based on Korean phonemic system and produce the natural lip-synch animation using the segmented phonemes.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.11a
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• pp.53-54
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• 2018

주어진 영상으로부터의 3 차원 얼굴 모델링은 얼굴 분석, 애니메이션, 생체 인식 등의 많은 컴퓨터비전 및 그래픽스 응용분야에서 중요한 역할을 하고 있다. 그 중에서도 헤어 영역은 얼굴에 비해 모양의 다양성과 모델의 복잡도가 현저히 높다. 기존의 연구는 주로 얼굴 영역에 한정한 3 차원 얼굴 모델링을 중심으로 이루어졌지만 헤어 모델링은 중요하게 다루지 않고 있는 경우가 많다. 본 논문에서는 심층인공신경망의 일종인 FCN (fully connected network)을 이용하여 인물 영상에서 헤어 부분을 영역화하고 그와 가장 유사한 3D 헤어 모델을 데이터베이스에서 검색하여 3 차원 얼굴 모델에 증강함으로써 완전한 얼굴 모델링을 수행하는 방법을 제안한다. 이는 FCN 을 이용하여 다양한 인물 영상에 대하여 네트워크 학습을 수행하는 과정과 3D 헤어 데이터베이스의 구축 과정을 포함한다. 실험 결과 적절한 수준의 헤어 모델이 3 차원 얼굴 모델링 결과물에 증강됨을 확인하였다.

• The Journal of the Korea Contents Association
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• v.7 no.4
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• pp.160-169
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• 2007

Main problem in the domestic motion capture type production is that motion data are used even in the case when the human sensibility is needed. In other words it fails to give human images to the work, and production method only use motion capture data unconditionally and impetuously. Even though motion capture is effective and are various and applicable to various areas, it would cause enormous lose of capital and manual labor if these problems are not solved. In the present study, we compare motion capture with key animation production and analyze the merits and short comings of them. Also, we analyze them through the actual production and present the efficient method of key animation production when the expensive motion capturing devices are not available.

• 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.

• 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 the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.21-28
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• 2007

The facial modeling and animation technology had been studied in computer graphics field. The facial modeling technology is utilized much in virtual reality research purpose of MPEG-4 and so on and movie, advertisement, industry field of game and so on. Therefore, the development of 3D facial model that can do interaction with human is essential to little more realistic interface. We developed realistic and convenient 3D facial modeling system that using a optional facial image only. This system allows easily fitting to optional facial image by using the Korean standard facial model (generic model). So it generates intuitively 3D facial model as controling control points elastically after fitting control points on the generic model wire to the optional facial image. We can confirm and modify the 3D facial model by movement, magnify, reduce and turning. We experimented with 30 facial images of $630{\times}630$ sizes to verify usefulness of system that developed.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.11b
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• pp.597-600
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• 2003

이 연구에서는, 움직임이 커서 확실하게 움직임의 변화를 확인할 수 있는 입 주변의 움직임보다 움직임이 세밀하고 다양해 표현하기가 까다로울 수 있는 눈 주변의 움직임에 있어서 눈 주변의 세밀한 움직임의 근육을 잡는 것과 움직임의 기준정, 또 타겟들의 적절한 조합이 중요한 요소가 된다고 보고 절기에 근거를 두어 블렌드쉐이프를 적용하여 표정 타겟을 만들어 눈 주변의 표정에 대한 연구를 하여 3D얼굴 애니메이션에 적용시키는 방법으로 페이셜 애니메이션 중에서도 눈 주변의 움직임을 중심으로 제안한다.

• Proceedings of the Korea Contents Association Conference
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• 2014.11a
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• pp.169-170
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• 2014

컴퓨터 그래픽의 발달로 3D 애니메이션은 시각적 리얼리티와 화려한 영상미로 애니메이션 특유의 비현실적인 상황과 허구적 캐릭터가 주는 재미를 관객에게 전한다. 특히 캐릭터의 얼굴 표정은 관객과의 감정 소통과 의사전달에 중요한 정보로서 디테일한 연기를 필요로 한다. 이에 3D 애니메이션 캐릭터의 경우 페이셜에 다양한 기능들이 요구되며, 일반적인 블렌드 쉐입과 클러스터 외에도 만화적 표현을 위한 다양한 기술들이 사용된다. 기존의 공정 과정에는 한 페이셜에 이러한 모든 기능들이 접목되어 복잡하며 까다로운 페이셜 리깅 공정이 이뤄진다. 본 연구에서는 기존의 공정들에서 한정되게 사용되었던 블렌드 쉐입을 이용하여 다양한 기능들을 타겟팅하는 레이어 방식을 통해 효율적인 페이셜 리깅 공정을 연구하고자 한다.

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.21 no.7
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• pp.18-23
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• 2003

• 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.