Remeshing and spatio-temporal wavelet filtering for 3D animations

In this paper, we present a new framework to analyse and process 3D animations (defined by sequences of triangular meshes sharing the same connectivity at any frame). Our idea is to develop a spatio-temporal wavelet filtering for such data, leading to a relevant multiresolution decomposition. In geometry processing, the most efficient spatial wavelets are based on a semiregular sampling. Since the 3D animations generally have an irregular sampling, one of our contribution is a remeshing technique, transforming an animation in a sequence of semiregular meshes, which presents regularity in time but also in space. This new sampling has the advantage to improve the quality of the multiresolution decomposition in the spatial dimension. To show the contribution of such a spatio-temporal filtering in animation processing, we present some experimental results in data compression.