Master thesis done at DICE by Kristoffer Jonsson from Uppsala University.
The aim for this thesis is to develop a foundation for a compression system for animated mesh sequences, specifically under dynamic change of mesh geometry and
topology. Compression of mesh sequences is of special interest in the game industry and this particular thesis is a part of an ongoing series of projects at EA DICE.
One of the primary challenges when creating a mesh compression system is creating a matching bijective subset of the mesh surfaces between two subsequent frames in the
animation to guide remeshing of the sequence. This thesis describes a method for producing a bijective set of matching mesh patches between two meshes along with
an error metric that captures the quality of the matching in terms of shape similarity and distortion.
Theory of mathematical topology and tensor algebra used in methods for high performance scientific digital 3D-image recognition are here adopted to extract similar local features between meshes. Techniques for creating parametrizations of mesh patches are combined with techniques for matching point clouds and deforming mesh geometry under energy minimization in order to produce a matching set of patches.
The presented algorithm successfully creates bijective sets of matched patches for subsequent meshes in a sequence as well as measures the error for the matchings. Results show an average matching set size of approximately 25% of the mesh areas over a sequence of meshes. This suggests that the data size of such a sequence could potentially be reduced by 25%.