Animating facial expressions

Platt, Stephen M.; Badler, Norman I.

doi:10.1145/965161.806812

Cited by 248 publications

(104 citation statements)

References 6 publications

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“…We use a face model which is an elaboration of the facial mesh developed by Platt and Badler [27]. We extend this into a topologically invariant physics-based model by adding anatomically-based muscles to it [11].…”

Section: Facial Modelingmentioning

confidence: 99%

Coding, analysis, interpretation, and recognition of facial expressions

Essa

Pentland

1997

IEEE Trans. Pattern Anal. Machine Intell.

747

378

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Section: Facial Modelingmentioning

confidence: 99%

Coding, analysis, interpretation, and recognition of facial expressions

Essa

Pentland

1997

IEEE Trans. Pattern Anal. Machine Intell.

747

378

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“…Platt and Badler [18] pioneered muscle-based model since 1980s. They proposed a mass-spring model to connect the skin, muscle and bone nodes.…”

Section: Muscle-based Modellingmentioning

confidence: 99%

Computer Facial Animation: A Review

Ping¹,

Abdullah²,

Sulaiman³

et al. 2013

IJCTE

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Abstract-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 concepts and problems for each technique are highlighted in the paper.Index Terms-Computer graphics, data-driven animation, facial animation, geometric-based modelling. I. INTRODUCTIONComputer facial animation is experiencing a continuous and rapid growth since the pioneering work of Frederick I. Parke [1] in 1972. This is partly due to the increasing demand of virtual characters or avatars in the field of gaming, filming, human computer interaction and human machine communication.The human face is one of the channels in expressing the affective states. It has complex but flexible three-dimensional (3D) surfaces. To present the human face onto a computer system is a challenging task due to several goals to be achieved. According to Deng and Noh [2], the main goal in facial modelling and animation research is to develop a high adaptability system that creates realistic animation in real time mode where decreasing manual handling process. Here, high adaptability refers to the system that is easily adapted to any individuals" face.Various approaches have been proposed by the research community to improve the performance of facial animation in different aspects. Some claims that a good facial modelling and animation involving how to lip synchronization and how to use the eyes, brows and lids for expression [3]. Others believed that a facial model should include other attributes such as surface colours and textures [4].The focus of this paper is to present a review of the past and recent advancements in facial animation research. Besides, an overview of the facial animation framework is discussed to give a picture of where the modelling and animation techniques take place. The goal of this review is to improve the current computer facial animation system with the knowledge of the current advancement in this technology. II. A GENERAL FACIAL ANIMATION FRAMEWORKAnimating facial action is a tedious and complicated task. The construction of facial animation proceeds in several stages and is shown in Fig. 1. Each facial animation starts from the head model creation. The facial geometry is created from the input data either captured from images or motions. The input data are pre-processed and filtered, only the corresponding data is used to create the basis of morphable meshes. Next, geometric-based modelling is a...

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“…In the early work of soft tissue simulation, static solutions of deformation were sought considering the balance of force at given external conditions, without taking into account the dynamic effects in the temporal domain [2]. Since the pioneering work by Terzopoulos et al in the simulation of elastically deformable models [3], simulating the dynamics of soft tissue deformation in the temporal domain has become widely recognized for achieving physically correct and visually realistic simulations [4].…”

Section: Introductionmentioning

confidence: 99%

Cellular neural network modelling of soft tissue dynamics for surgical simulation

Zhang

Zhong

Smith

et al. 2017

THC

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Abstract. BACKGROUND: Currently, the mechanical dynamics of soft tissue deformation is achieved by numerical time integrations such as the explicit or implicit integration; however, the explicit integration is stable only under a small time step, whereas the implicit integration is computationally expensive in spite of the accommodation of a large time step. OBJECTIVE: This paper presents a cellular neural network method for stable simulation of soft tissue deformation dynamics. METHOD: The non-rigid motion equation is formulated as a cellular neural network with local connectivity of cells, and thus the dynamics of soft tissue deformation is transformed into the neural dynamics of the cellular neural network. RESULTS: Results show that the proposed method can achieve good accuracy at a small time step. It still remains stable at a large time step, while maintaining the computational efficiency of the explicit integration. CONCLUSION: The proposed method can achieve stable soft tissue deformation with efficiency of explicit integration for surgical simulation.

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Animating facial expressions

Cited by 248 publications

References 6 publications

Coding, analysis, interpretation, and recognition of facial expressions

Coding, analysis, interpretation, and recognition of facial expressions

Computer Facial Animation: A Review

Cellular neural network modelling of soft tissue dynamics for surgical simulation

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