Bayesian AD coder: Mesh-aware valence coding for multiresolution meshes

The Alliez Desbrun (AD) coder has accomplished the best compression ratios for multiresolution 2-manifold meshes in the last decade. This paper presents a Bayesian AD coder which has better compression ratios in connectivity coding than the original coder, based on a mesh-aware valence coding scheme for multiresolution meshes. In contrast to the original AD coder, which directly encodes a valence for each decimated vertex, our coder indirectly encodes the valence according to its rank in a sorted list with respect to the mesh-aware scores of the possible valences. Experimental results show that the Bayesian AD coder shows an improvement of 8.5-36.2% in connectivity coding compared to the original AD coder despite of the fact that a simple coarse-to-fine step of the mesh-aware valence coding is plugged into the original algorithm.