Waters' abstract muscles model
I wrote this page just after the third year of my degree (2001) and
I did not have the time to rewrite it.
The facial meshes used for this project come from Gedalia Pasternak's web site: http://www.mindspring.com/~paster/ (THE EXPRESSION TOOLKIT).
The goal of this project was to study the abstract muscle-based model in order to show the operations needed to adapt it to different meshes. It was also to evaluate the quality of expressions and animations created by the deformation of the face through the muscle structure. The animation in real-time has been observed in a virtual environment created with the 3D engine Fly3d. To achieve this aim the Waters model is developed in C++. The polygon mesh adaptation and the creation of expressions and animations are done through an application developed with Microlsoft Visual C++.
In the Waters' model there are two types of abstract muscles.
The adaptation of a mesh to the muscle structure is important to be able to animate different faces (polygon mesh) with one set of parameters.Three steps are necessary:
The adaptation is a success if the facial expression on the new face is similar to the expression on the face model.
The goal of this project was to point out certain characteristics of an abstract muscle-based model implementation. This model could be used for a large range of virtual characters having different face topologies. However an adaptation of the character faces to the muscle structure needs to be done. This point is shown to be not a difficult task, as far as the human faces are concerned. The adaptation of a facial mask to the muscle structure takes about 40-60 minutes. This process enables the new faces to show the same recognisable expressions with the same system parameters (same muscle contractions). The adaptation for non-human faces could be done but the amount of work may be more important and the muscle structure may have to be changed. The face deformation through the abstract muscle-based model appears to be intuitive and enable the creation of a very large range of expressions. Several defaults on the appearance of the faces have been noticed due to the coarse approximation of the facial anatomy. However it remains possible to improve the model and its implementation to reduce these issues. The facial animation, done by linear interpolation on the muscle contractions, results to satisfactory appearance. As far as the efficiency of animations is concerned, the face complexity can be an important factor of deterioration but the use of reasonably detail face achieves to fairly good performances.