Abstract muscle action procedures for human face animation

Magnenat‐Thalmann, Nadia; Primeau, E.; Thalmann, Daniel

doi:10.1007/bf01914864

Cited by 158 publications

(51 citation statements)

References 16 publications

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“…Here, we want to highlight a few approaches that have been taken to produce three-dimensional face animations (for a well-known example of highly realistic two-dimensional animation see [Ezzat et al 2002]). The earliest attempts at three-dimensional animation were based on abstract muscle parameterizations [Parke 1982;Magnenat-Thalmann et al 1988], as well as physical modeling of facial muscles using spring-masssystems [Terzopoulus and Waters 1990]. These were later extended to include skin deformations [Köhler et al 2002].…”

Section: Facial Animation and Realismmentioning

confidence: 99%

Psychophysical evaluation of animated facial expressions

Wallraven

Breidt

Cunningham

et al. 2005

Proceedings of the 2nd Symposium on Applied Perception in Graphics and Visualization

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The human face is capable of producing an astonishing variety of expressions-expressions for which sometimes the smallest difference changes the perceived meaning noticably. Producing realisticlooking facial animations that are able to transport this degree of complexity continues to be a challenging research topic in computer graphics. One important question that remains to be answered is: When are facial animations good enough? Here we present an integrated framework in which psychophysical experiments are used in a first step to systematically evaluate the perceptual quality of computer-generated animations with respect to real-world video sequences. The result of the first experiment is an evaluation of several animation techniques in which we expose specific animation parameters that are important for perceptual fidelity. In a second experiment we then use these benchmarked animations in the context of perceptual research in order to systematically investigate the spatio-temporal characteristics of expressions. Using such an integrated approach, we are able to provide insights into facial expressions for both the perceptual and computer graphics community.

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Section: Facial Animation and Realismmentioning

confidence: 99%

Psychophysical evaluation of animated facial expressions

Wallraven

Breidt

Cunningham

et al. 2005

Proceedings of the 2nd Symposium on Applied Perception in Graphics and Visualization

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“…[Platt and Badler 1981] built a face model using masses and springs including forces generated by muscles, and made use of the Facial Action Coding System (FACS) [Ekman and Friesen 1978]. Other early work included [Waters 1987;Magnenat-Thalmann et al 1988;Kalra et al 1992]. [Lee et al 1995] constructed an anatomically motivated facial model based on scanned data, and endowed it with a mass spring system driven by muscle contractions.…”

Section: Related Workmentioning

confidence: 99%

Automatic determination of facial muscle activations from sparse motion capture marker data

Sifakis

Neverov

Fedkiw

2005

ACM SIGGRAPH 2005 Papers

161

174

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We built an anatomically accurate model of facial musculature, passive tissue and underlying skeletal structure using volumetric data acquired from a living male subject. The tissues are endowed with a highly nonlinear constitutive model including controllable anisotropic muscle activations based on fiber directions. Detailed models of this sort can be difficult to animate requiring complex coordinated stimulation of the underlying musculature. We propose a solution to this problem automatically determining muscle activations that track a sparse set of surface landmarks, e.g. acquired from motion capture marker data. Since the resulting animation is obtained via a three dimensional nonlinear finite element method, we obtain visually plausible and anatomically correct deformations with spatial and temporal coherence that provides robustness against outliers in the motion capture data. Moreover, the obtained muscle activations can be used in a robust simulation framework including contact and collision of the face with external objects.

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“…Most of the existing parametric models of the human face have been developed in the perspective of optimizing the visual rendering of facial expressions (Parke, 1974;Platt & Badler, 1981;Bergeron & Lachapelle, 1985;Waters, 1987;Magnenat-Thalmann, Primeau, et al, 1988;Viaud & Yahia, 1992). Few models have focused on the specific articulation of speech gestures: Saintourens, Tramus, et al (1990); Benoît, Lallouache, et al (1992); Henton and Litwinovitz (1994) prestored a limited set of facial images occurring in the natural production of speech in order to synchronize the processes of diphone concatenation and visemes display in a text-to-audio-visual speech synthesizer.…”

Section: Future Directionsmentioning

confidence: 99%