K. Waters and J. Frisbie. A Coordinated Muscle Model for Speech Animation. In Proc. Graphics Interface '95, pages 163--170, May 1995.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....a limited repertoire of motions [10] To their credit, these models are mostly in 3D. For many of the models, though, the control parameters are defined by hand. A few are based on the actual physics of the lips: they attempt to model the physical material and musculature in the mouth region [8] [16]. Unfortunately, themusculature of the lips is extremely complicated and has proved to be very difficult to model accurately. The basic physiology is comprised of an ellipsoidal muscle (the Obicularis oris) surrounding the mouth and several muscles which push and pull on this ring. This ....

....all of these facial muscles: the observed set of facial motions seem to be a slim subspace of the full range implied bythemuscles. Some models, as in the work by Frisbie and Waters, have tried to approximate this subspace by modeling key lip positions (visemes) and then interpolating between them [16]. However, This limits the correct set of lip shapes to those fit by hand, without modeling how the lips really movebetween them. I hope to fill the gap in these approaches with a 3D model that can be used for both analysis and synthesis. My approach is to start with a 3D shape model and ....

K. Waters and J. Frisbie. "A Coordinated Muscle Model for Speech Animation". In Graphics Interface, pages 163--170, 1995.

....(VLBV 98) Urbana, Illinois. October, 1998. their credit, these models are mostly in 3D. For many of the models, though, the control parameters are defined by hand. A few are based on the actual physics of the lips: they attempt to model the physical material and musculature in the mouth region [7]. Unfortunately, the musculature of the mouth is extremely complicated and has proved to be very difficult to model accurately. Even if the modeling were accurate, this approach would still result in a difficult control problem. We hope to fill the gap in these approaches with our learned 3D ....

K. Waters and J. Frisbie. "A Coordinated Muscle Model for Speech Animation". In Proceedings of Graphics Interface '95, pages 163--170, Ontario, Canada, May 1995.

....1 Wrinkles, for example arise and disappear, so tracking them is futile. Pose Estimation 2D 3D Conversion Volume Morphing Classification Reconstruction Appearance Sampling There exists a large number of works in facial animation based on geometry deformation. Vector based muscle models [14, 18] offer simple and compact representations, however no automatic means of placing muscles within a person specific mesh have been reported. Other deformation methods include spline models [19, 20] and free form deformations [21, 22] See [9] for an excellent survey of these and other methods. ....

K. Waters, J. Frisbie, A Coordinated Muscle Model for Speech Animation, Graphics Interface, 1995, pp. 163 -- 170

....clear, and flexible control box containing a 3D grid of control points. As the control box is squashed, bent, or twisted into arbitrary shapes, the embedded mesh deforms accordingly. The basis for the control points is a tri variate tensor product Bernstein polynomial. Vector based muscle models [27, 28] are adapted widely for their compact representation. A delineated deformation field models the action of muscles upon skin. The muscle definition includes the vector field direction, an origin, and an insertion point. The cone shaped field extent is defined by cosine functions and fall off ....

....localize the deformations. Our approach provides unique advantages over existing methods for creating facial animation. First, most existing approaches require animation mechanisms (e.g. muscles, or FFD) explicitly embedded in the facial mesh. For example, muscles must be placed under the mesh [27, 28], or spring and stiffness constants must be determined in advance [2] and tuned each time a new face mesh is created. In contrast, our RBF method works on any mesh without modification. Second, the creation of facial animations can be easily automated with our method. When video data of an actor ....

K. Waters, J. Frisbie, A Coordinated Muscle Model for Speech Animation, Graphics Interface, 1995, 163 -- 170

....by a combination of independent parameter values [85 pp. 188] Unlike interpolation techniques, parameterizations allow explicit control of specific facial configurations. Combinations of parameters provide a large range of facial expressions with relatively low computational costs. As Waters [128] indicates, there is no systematic way to arbitrate between two conflicting parameters to blend expressions that effect the same vertices, hence parameterization rarely produces natural human expressions or configurations when a conflict between parameters occurs. For this reason, ....

....and models it with a simple spring mass system. Browman et al. 17] showed the control of vocal tract simulation with two mass spring systems. One spring controlled the lip aperture and the other the protrusion. Exploiting the simplicity and generality of mass spring systems, Waters et al. [128] develop a twodimensional mouth muscle model and animation method. Since mouth animation is generated from relatively few muscle actions, motion realism is largely independent of the number of surface model elements. Texture mapping provides additional realism for simple geometric mouth models. ....

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K. Waters, J. Frisbie, A Coordinated Muscle Model for Speech Animation, Graphics Interface, 1995 pp. 163 -- 170

....a generic mesh in a preprocessing step [8] 15] 18] 24] The generic mesh contains all the animation parameters necessary for the subsequent person specific animations. The model is animated by mesh node displacements based on motion rules specified by deformation engine such as vector muscles [25][26] spring muscles [15] 19] free form deformations [13] volume morphing [10] or simple interpolation [18] Texture mapping [10] 15] 18] is employed to improve realism with characteristics such as skin wrinkles that are hard to achieve by geometric deformations alone. Such 3D approaches hold ....

K. Waters, J. Frisbie, A Coordinated Muscle Model for Speech Animation, Graphics Interface, 1995 pp. 163 -- 170

....Deformations, Facial animation, Morphing, Neural Nets 1 Introduction Facial animation aims at producing expressive and plausible animations of a 3D face model. Some approaches model the anatomy of the face, deriving facial animations from the physical behaviors of the bone and muscle structures [16, 24, 30, 31]. Others focus only on the surface of the face, using smooth surface deformation mechanisms to create facial expressions [11, 12, 23] In general, these approaches make little use of existing data for animating a new model. Each time a new model is created for animation, a method specific tuning ....

....will take similar efforts. A parametric approach associates the motion of a group of vertices to a specific parameter [22] This manual association must be repeated for models with different mesh structures. Vector based muscle models place the heuristic muscles under the surface of the face [30, 31]. This process is repeated for each new model and no automatic placement strategy has been reported except for the case where a new model has the same mesh structure. Muscle contraction values are transferable between models only when the involved models are equipped with properly positioned ....

K. Waters, J. Frisbie, A Coordinated Muscle Model for Speech Animation, Graphics Interface, 1995, 163 170

....1 Wrinkles, for example arise and disappear, so tracking them is futile. Volume Morphing Classification Reconstruction Appearance Sampling Pose Estimation 2D 3D Conversion There exists a large number of works in facial animation based on geometry deformation. Vector based muscle models [14, 18] offer simple and compact representations, however no automatic means of placing muscles within a person specific mesh have been reported. Other deformation methods include spline models [19, 20] and free form deformations [21, 22] See [9] for an excellent survey of these and other methods. ....

K. Waters, J. Frisbie, A Coordinated Muscle Model for Speech Animation, Graphics Interface, 1995, pp. 163 -- 170

....part of the face that is influenced by speech, this analysis is quite detailed. By directly learning the facial deformations from real speech, their parameterisation in terms of principal components is a natural and perceptually relevant one. This seems less the case for anatomically based models [10, 20]. Concatenation of visemes yields realistic animations. In addition, the results yield a robust face tracker for performance capture, that works without special markers. The structure of the paper is as follows. Section 2 describes how the 3D face shapes are acquired that are observed during ....

K. Waters and J. Frisbie. A coordinated muscle model for speech animation. In Graphics Interface, pages 163--170, 1995. 8

....our findings in FRED, a multi agent conversational system that establishes where the user looks by means of a desk mounted LC Technologies eyetracking system [4] In FRED, multiple conversational agents can be embodied by means of 3D texture mapped models of humanoid faces. Based on work by Waters [8], muscle models are used for generating accurate 3D facial expressions. The system uses our SCHISMA speech recognition and production engine to converse with the user [5] Each agent is capable of detecting whether the user is looking at it, and combines this information with speech data to ....

Waters, K. and Frisbee, J. A coordinated muscle model for speech animation. In Proceedings of Graphics Interface'95. Canada, 1995.

....a limited repertoire of motions [10] To their credit, these models are mostly in 3D. For many of the models, though, the control parameters are defined by hand. A few are based on the actual physics of the lips: they attempt to model the physical material and musculature in the mouth region [8] [15]. Unfortunately, the musculature of the lips is extremely complicated and has proved to be very difficult to model accurately. The basic physiology is comprised of an ellipsoidal muscle (the Obicularis oris) surrounding the mouth and several muscles which push and pull on this ring. This ....

....of these facial muscles: the observed set of facial motions seem to be a slim subspace of the full range implied by the muscles. Some models, as in the work by Frisbie and Waters, have tried to approximate this subspace by modeling key lip positions (visemes) and then interpolating between them [15]. However, this limits the accuracy of the resulting lip shapes, since the only shapes learned from data are those for the static viseme poses. We hope to fill the gap in these approaches with a 3D model that can be used for both analysis and synthesis. Our approach is to start with a 3D shape ....

K. Waters and J. Frisbie. "A Coordinated Muscle Model for Speech Animation". In Graphics Interface, pages 163-- 170, 1995.

....a limited repertoire of motions [10] To their credit, these models are mostly in 3D. For many of the models, though, the control parameters are defined by hand. A few are based on the actual physics of the lips: they attempt to model the physical material and musculature in the mouth region [8] [16]. Unfortunately, the musculature of the lips is extremely complicated and has proved to be very difficult to model accurately. The basic physiology is comprised of an ellipsoidal muscle (the Obicularis oris) surrounding the mouth and several muscles which push and pull on this ring. This ....

....of these facial muscles: the observed set of facial motions seem to be a slim subspace of the full range implied by the muscles. Some models, as in the work by Frisbie and Waters, have tried to approximate this subspace by modeling key lip positions (visemes) and then interpolating between them [16]. However, This limits the correct set of lip shapes to those fit by hand, without modeling how the lips really move between them. I hope to fill the gap in these approaches with a 3D model that can be used for both analysis and synthesis. My approach is to start with a 3D shape model and ....

K. Waters and J. Frisbie. "A Coordinated Muscle Model for Speech Animation". In Graphics Interface, pages 163--170, 1995.

....a limited repertoire of motions [8] To their credit, these models are mostly in 3D. For many of the models, though, the control parameters are defined by hand. A few are based on the actual physics of the lips: they attempt to model the physical material and musculature in the mouth region [6] [12]. Unfortunately, the musculature of the mouth is extremely complicated and has proved to be very difficult to model accurately. Even if the modeling were accurate, this approach would still result in a difficult control problem. Humans do not have independent control of all of these facial ....

....control problem. Humans do not have independent control of all of these facial muscles: normal motions are a slim subspace of the possible muscle states. Some models have tried to approximate this subspace by modeling key lip positions (visemes) and then interpolating between them (for example [12]) However, this limits the accuracy of the resulting lip shapes, since only the key positions are learned from data. We hope to fill the gap in these approaches with a 3D model that can be used for both analysis and synthesis. Our approach is to start with a 3D shape model and generic physics. We ....

K. Waters and J. Frisbie. "A Coordinated Muscle Model for Speech Animation". In Graphics Interface, pages 163-- 170, 1995.

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K. Waters and J. Frisbie. A Coordinated Muscle Model for Speech Animation. In Proc. Graphics Interface '95, pages 163--170, May 1995.

No context found.

K. Waters and J. Frisbie. A Coordinated Muscle Model for Speech Animation. In Proc. Graphics Interface '95, pages 163--170, May 1995.

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K. Waters and J. Frisbie, A coordinated muscle model for speech animation, in Graphics Interface, pp. 163170, 1995.

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Keith Waters and J. Frisbie, "A Coordinated Muscle Model for Speech Animation", Graphics Interface '95, pp.163-170(1995)

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