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About 491 papers for “Computer facial animation”
Frederic I. Parke, Keith Waters · 2008
This comprehensive work provides the fundamentals of computer facial animation and brings into sharper focus techniques that are becoming mainstream in the industry. Over the past decade, since the publication of the first edition, there have been significant developments by academic research groups and in the film and games industries leading to t
Cited by 87
Frederic I. Parke · PsycEXTRA Dataset · 1997
Cited by 310
Heng Ping, Lili Nurliyana Abdullah, Puteri Suhaiza Sulaiman et al. · International Journal of Computer Theory and Engineering · 2013
Computer facial animation is not a new endeavour as it had been introduced since 1970s. However, animating human face still presents interesting challenges because of its familiarity as the face is the part used to recognize individuals.Facial modelling and facial animation are important in developing realistic computer facial animation. Both modelling and animation is dependent to drive the animation.This paper reviews several geometric -based modelling (shape interpolation,parameterization and muscle-based animation)and data-driven animation (image-based techniques speech-driven techniques and performance-driven animation) techniques used in computer graphics and vision for facial animation. The main concept s and problems for each technique are highlighted in the paper.
Cited by 21
Frederic I. Parke, Keith Waters · Medical Entomology and Zoology · 1996
This book integrates all aspects of computer-generated facial animation including computer-based visualization techniques, three-dimensional character animation, anatomical, and psychological considerations and discusses them in the framework of promising applications in entertainment, human-computer interface, research, and education.
Cited by 582
Steve Maddock, James Edge, Manuel Sanchez · 2008
Static and dynamic realism are both important in computer facial animation. However, for embodied conversational agents in interfaces, and for agents or avatars in virtual environments, movement and behaviour are more important than photorealism. In this paper we summarise our work on two systems that feature aspects of this dynamic realism: coarticulation for visual speech and facial tissue deformation producing expressions and wrinkles.
Cited by 0
Choong Seng Chan · DR-NTU (Nanyang Technological University) · 2010
Computer facial animation still remains a very challenging topic within the computer graphics \ncommunity. In this project, a realistic and expressive computer facial animation system \nis developed by automated learning from Vicon system facial motion capture data. Data \ncaptured from real speaker are used which would make the mapped facial animation more \nnatural and lifelike. The dimensions of facial motion capture data with different emotions \nare collected using Vicon Nexus are reduced using dimensionality reduction techniques. \nThe purpose of reduce the dimensions of the data is to prepare them to be used in the \nconstruction of the Phoneme-Independent Expression Eigenspace (PIEES) in the modeling \nstage. Programs are written using Matlab to perform dimensionality reduction techniques \non the data. The quality of the resulting data is evaluated by computing the Root Mean \nSquare Error. After that, the resulting data from Matlab is converted to .C3D format using \nC3Deditor. Ultimately, the emotions data in .C3D format are mapped to a 3D animated \nface using Autodesk MotionBuilder 2009. Our experiments demonstrate that the approach \npresented can effectively synthesize realistic expressive facial animation. The approach \npresented can be used for various applications to generate natural expressive and realistic \nfacial animation, for example, generating a personal avatar for different users.
Cited by 0
Linghua Li, Yongkui Liu, Hengbo Zhang · 2012
This paper describes and surveys the techniques used in facial animation. The techniques are discussed from two aspects: the techniques of facial modeling and the techniques of data acquirement of facial animation. The techniques of facial modeling are classified into four categories: shape interpolations, parameterizations, muscle-based modeling and pseudo-muscle-based models. And the techniques of animation data acquirement are classified into three categories: speech-driven techniques, image-based techniques and data-capture techniques. The generation, the main ideas, the historical use, and the strength and weakness of each technique are described in detail.
Cited by 14
Zhigang Deng, Junyong Noh · 2008
Since the pioneering work of Frederic I. Parke [1] in 1972, significant research efforts have been attempted to generate realistic facial modeling and animation. The most ambitious attempts perform the face modeling and rendering in real time. Because of the complexity of human facial anatomy and our
Cited by 0
Manjula Patel · Computer Graphics Forum · 1995
Abstract In everyday interactions with one another we use the face for recognising people and for communicating with them. Despite the considerable amount of research into computer generated facial animation, one particular aspect, that of the colouration of the face appears to have been neglected. In this paper we address issues pertinent to the use of colour for both modelling the appearance of the face and for enhancing communication during facial expression and animation. Colouration is an integral part of the face, which helps in the recognition of faces as well as in the interpretation of the often subtle signals emitted by the human face.
Cited by 8
Keith Waters · Middlesex University Research Repository (Middlesex University Of London) · 1988
This present research is concerned with the design, development and implementation of three-dimensional \ncomputer-generated facial images capable of expression \ngesture and speech. \nA review of previous work in chapter one shows that to date \nthe model of computer-generated faces has been one in which \nconstruction and animation were not separated and which \ntherefore possessed only a limited expressive range. It is \nargued in chapter two that the physical description of the \nface cannot be seen as originating from a single generic \nmould. Chapter three therefore describes data acquisition \ntechniques employed in the computer generation of free-form \nsurfaces which are applicable to three-dimensional faces. \nExpressions are the result of the distortion of the surface \nof the skin by the complex interactions of bone, muscle and \nskin. Chapter four demonstrates with static images and short \nanimation sequences in video that a muscle model process \nalgorithm can simulate the primary characteristics of the \nfacial muscles. \nThree-dimensional speech synchronization was the most \ncomplex problem to achieve effectively. Chapter five \ndescribes two successful approaches: the direct mapping of \nmouth shapes in two dimensions to the model in three \ndimensions, and geometric distortions of the mouth created \nby the contraction of specified muscle combinations. \nChapter six describes the implementation of software for \nthis research and argues the case for a parametric approach. \nChapter seven is concerned with the control of facial \narticulations and discusses a more biological approach to \nthese. Finally chapter eight draws conclusions from the \npresent research and suggests further extensions.
Cited by 6Open access
Marco Enrique, Zavala Chmelicka, Nancy Amato et al. · 2005
Chair of Advisory Committee: Dr. Ricardo Gutierrez-Osuna Facial animations capable of articulating accurate movements in synchrony with a speech track have become a subject of much research during the past decade. Most of these efforts have focused on articulation of lip and tongue movements, since these are the primary sources of information in speech reading. However, a wealth of paralinguistic information is implicitly conveyed through visual prosody (e.g., head and eyebrow movements). In contrast with lip/tongue movements, however, for which the articulation rules are fairly well known (i.e., viseme-phoneme mappings, coarticulation), little is known about the generation of visual prosody. The objective of this thesis is to explore the perceptual contributions of visual prosody in speech-driven facial avatars. Our main hypothesis is that visual prosody driven by acoustics of the speech signal, as opposed to random or no visual prosody, results in more realistic, coherent and convincing facial animations. To test this hypothesis, we have developed an audio-visual system capable of capturing synchronized speech and facial motion from a speaker using infrared illumination and retro-reflective markers. Iniv
Cited by 0
Samuel Gandang Gunanto, Mochamad Hariadi, Eko Mulyanto Yuniarno · 2016
High demand on the productivity of the animation industry in Indonesia requires a change in the existing production process. Motion capture technology is the implementation of a computer vision principle to adopt the human eye senses to understand the phenomenon of motion results from a camera and mapped the virtual movement patterns. This paper will discuss a method for tracking marker features in the human face to obtain information about facial expressions. The tracking technique is using implementation of temporal coherence principle. This research assumes that using temporal coherence approach, the tracking process in sequential images can be simplified by calculating similarity on markers in each frame. The results show this feature-tracking process have reliable results to handle a lot of frames. Computation used very efficiently and cheap because it does not require a learning process in advance. The precision accuracy of tracking parameters generated a database of good visual expression.
Cited by 0
M. Courgeon, Céline Clavel · Journal on Multimodal User Interfaces · 2013
Cited by 31
Sagar, Mark, Scott, R · ResearchSpace (University of Auckland) · 2004
A motion tracking system enables faithful capture of subtle facial and eye motion using a surface electromyography (EMG) detection method to detect muscle movements and an electrooculogram (EOG) detection method to detect eye movements. An embodiment of the motion tracking animation system comprises a plurality of pairs of EOG electrodes adapted to be affixed to the skin surface of the performer at locations adjacent to the performer's eyes. The EOG data comprises electrical signals corresponding to eye movements of a performer during a performance. Programming instructions further provide processing of the EOG data and mapping of processed EOG data onto an animated character. As a result, the animated character will exhibit he same muscle and eye movements as the performer.
Cited by 1
Demetri Terzopoulos £ýþ, Keith Waters Ý · 2008
We develop a new 3D hierarchical model of the human face. The model incorporates a physically-based approximation to facial tissue and a set of anatomically-motivated facial muscle actuators. Despite its sophistication, the model is efficient enough to produce facial animation at interactive rates on a high-end graphics workstation. A second contribution of this paper is a technique for estimating muscle contractions from video sequences of human faces performing expressive articulations. These estimates may be input as dynamic control parameters to the face model in order to produce realistic animation. Using an example, we demonstrate that our technique yields sufficiently accurate muscle contraction estimates for the model to reproduce expressions from dynamic images of faces.
Cited by 0
Joseph A. Johnson · 2021
Human communications rely on facial expression to denote mood, sentiment, and intent. Realistic facial animation of computer graphic models of human faces can be difficult to achieve as a result of the many details that must be approximated in generating believable facial expressions. Many theoretical approaches have been researched and implemented to create more and more accurate animations that can effectively portray human emotions. Even though many of these approaches are able to generate realistic looking expressions, they typically require a lot of artistic intervention to achieve a believable result. To reduce the intervention needed to create realistic facial animation, new approaches that utilize machine learning are being researched to reduce the amount of effort needed to generate believable facial animations. This survey paper summarizes over 20 research papers related to facial animation and compares the traditional animation approaches to newer machine learning methods as well as highlights the strengths, weaknesses, and use cases of each different approach.
Cited by 1Open access
D. A. Chechko, Alla V. Radionova · Informatics in school · 2018
One of the most difcult areas of 3D computer graphics is a facial animation. To create it, you need knowledge of facial muscles anatomy, methods and techniques of facial animation, skills in a 3D modeling software. The article describes facial animation tutorials in Blender. The tutorials introduce two methods of facial animation: using shape keys and motion tracking. The tutorials can be used at school, but requires basic Blender knowledge.
Cited by 1Open access
Christian Jones, S.S. Dlay · 1997
The research presents MARTI (Man-machine Animation Real-Time Interface) for the realisation of automated special effect animation and human computer interaction. MARTI introduces novel research in a number of engineering disciplines, which include speech recognition, facial modelling, and computer animation. This interdisciplinary research utilises the latest, hybrid connectionist/hidden Markov model system, providing very accurate phone recognition and timing for speaker independent continuous speech, and expands' knowledge from the animation industry in the development of accurate facial models and automated animation. The system uses simple vocal soundtracks of human speakers to provide lip synchronisation of computer graphical facial models, to realise the first natural interface and animation system capable of high performance for real users and real-world applications.
Cited by 3
Ferda Ofli, Of School · 2011
Multimodal signal analysis for learning and synthesis of human body and facial expressions by using techniques from speech/audio processing, 2D/3D computer vision, machine learning, pattern recognition, multimodal human-computer interaction, computer graphics, haptics and physically based simulations with specific focus on � audiovisual dance performance analysis for music-driven dance synthesis and animation � audiovisual facial expression analysis for prosody-driven facial expression synthesis and animation
Cited by 0
Matthew Brand · 1999
We introduce a method for predicting a control signal from another related signal, and apply it to voice puppetry: Generating full facial animation from expressive information in an audio track. The voice puppet learns a facial control model from computer vision of real facial behavior, automatically incorporating vocal and facial dynamics such as co-articulation. Animation is produced by using audio to drive the model, which induces a probability distribution over the manifold of possible facial motions. We present a lineartime closed-form solution for the most probable trajectory over this manifold. The output is a series of facial control parameters, suitable for driving many different kinds of animation ranging from video-realistic image warps to 3D cartoon characters. CR Categories: I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism---Animation; I.2.9 [Artificial Intelligence]: Robotics---Kinematics and Dynamics; I.4.8 [Image Processing and Computer Vision]: Scene ...
Cited by 0