• The KIPS Transactions:PartA
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• v.17A no.6
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• pp.281-288
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• 2010

In this paper, we describe the development of a system for generating a 3-dimensional human face using 3D scanned facial data and photo images, and morphing animation. The system comprises a facial feature input tool, a 3-dimensional texture mapping interface, and a 3-dimensional facial morphing interface. The facial feature input tool supports texture mapping and morphing animation - facial morphing areas between two facial models are defined by inputting facial feature points interactively. The texture mapping is done first by means of three photo images - a front and two side images - of a face model. The morphing interface allows for the generation of a morphing animation between corresponding areas of two facial models after texture mapping. This system allows users to interactively generate morphing animations between two facial models, without programming, using 3D scanned facial data and photo images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.8
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• pp.1310-1318
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• 2002

In this study, we developed a 3D facial modeler and animator that will not use the existing method by 3D scanner or camera. Without expensive image-input equipments, we can easily create 3D models only using front and side images. The system is available to animate 3D facial models as we connect to animation server on the WWW which is independent from specific platforms and softwares. It was implemented using Java 3D API. The facial modeler detects MPEG-4 FDP(Facial Definition Parameter) feature points from 2D input images, creates 3D facial model modifying generic facial model with the points. The animator animates and renders the 3D facial model according to MPEG-4 FAP(Facial Animation Parameter). This system can be used for generating an avatar on WWW.

• Journal of Korea Multimedia Society
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• v.17 no.9
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• pp.1076-1083
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• 2014

We propose an emotional facial avatar that portrays the user's facial expressions with an emotional emphasis, while achieving visual and behavioral realism. This is achieved by unifying automatic analysis of facial expressions and animation of realistic 3D faces with details such as facial hair and hairstyles. To augment facial appearance according to the user's emotions, we use emotional templates representing typical emotions in an artistic way, which can be easily combined with the skin texture of the 3D face at runtime. Hence, our interface gives the user vision-based control over facial animation of the emotional avatar, easily changing its moods.

• 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.

• Journal of Korea Multimedia Society
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• v.14 no.6
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• pp.813-823
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• 2011

This study is to suggest the facial animation methodology for that 3D character animators can use CGS system effectively during on their stage which they create ideas and use repeating a process of facial animation, it has suggested the CGS(Character Generation System) that is a creative idea generation methodology identified and complemented the problem of the existing computerized idea generation, in addition, this research being extended on the article vol.13, no.7, "CGS System based on Three-Dimensional Character Modeling II (Part2: About Digital Process)," on Korea Multimedia Society in July 2010 issue, Through the preceding study on 3D character facial expression according to character's feelings as an anatomical structure and the case study on character expressions of theatrical animation, this study is expected to have effectives as one method for maximization of facial animation and idea generation ability.

• 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.

• Journal of information and communication convergence engineering
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• v.21 no.2
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• pp.152-158
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• 2023

In recent years, as computer-generated imagery has been applied to more industries, realistic facial animation is one of the important research topics. The current solution for realistic facial animation is to create realistic rendered 3D characters, but the 3D characters created by traditional methods are always different from the actual characters and require high cost in terms of staff and time. Deepfake technology can achieve the effect of realistic faces and replicate facial animation. The facial details and animations are automatically done by the computer after the AI model is trained, and the AI model can be reused, thus reducing the human and time costs of realistic face animation. In addition, this study summarizes the way human face information is captured and proposes a new workflow for video to image conversion and demonstrates that the new work scheme can obtain higher quality images and exchange effects by evaluating the quality of No Reference Image Quality Assessment.

• 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.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.129-135
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• 2022

Real human digital models appear more and more frequently in VR/AR application scenarios, in which real-time markerless face capture animation of personalized virtual human faces is an important research topic. The traditional way to achieve personalized real human facial animation requires multiple mature animation staff, and in practice, the complex process and difficult technology may bring obstacles to inexperienced users. This paper proposes a new process to solve this kind of work, which has the advantages of low cost and less time than the traditional production method. For the personalized real human face model obtained by 3D reconstruction technology, first, use R3ds Wrap to topology the model, then use Avatary to make 52 Blend-Shape model files suitable for AR-Kit, and finally realize real-time markerless face capture 3D real human on the UE4 platform facial motion capture, this study makes rational use of the advantages of software and proposes a more efficient workflow for real-time markerless facial motion capture of personalized 3D real human models, The process ideas proposed in this paper can be helpful for other scholars who study this kind of work.

• 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.