In this paper, we propose an efficient method to generate optimal multiresolution models for deforming mesh sequence. By this method we define the importance degree of a triangle to be embedded into the quadric error metric (QEM) as a weight parameter, so that the new metric cannot only measure distance error but also reflect geometric variation of local areas. We append a deformation degree weight to the aggregated edge contraction cost for the whole animation. This new metric can preserve not only the model's individual geometric features, but also the features only appeared during the deforming animation. In addition, a mesh optimization method has also been proposed to allow visual distortion of the simplified models to be further alleviated. Our approach is efficient in operation, easy for implementation, and as a result a good quality of dynamic approximations with well-preserved fine details can be generated at any given frame on average.
A mesh optimization method using machine learning technique and variational mesh adaptation
