Being in an internet era, the rapid transmission of 3D mesh models is getting more important and efforts toward the compression of various aspects of mesh models have been provided. Even though a mesh model usually consists of coordinates of vertices and properties such as colors and normals, topology plays the most important part in the compression of other information in the models. Despite the extensive studies on Edgebreaker, the most frequently used and rigorously evaluated topology compressor, the probability distribution of its five op-codes, C, R, E, S, and L, has never been rigorously analyzed yet. In this paper, we present probability distribution of the op-codes which is useful for both the optimization of the compression performance and a priori estimation of compressed file size.

As the transmission of 3D shape models through Internet becomes more important, the compression issue of shape models gets more critical. The issues for normal vectors have not yet been explored as much as it deserves, even though the size of the data for normal vectors can be significantly larger than its counterparts of topology and geometry. Presented in this paper is an approach to compress the normal vectors of a shape model represented in a mesh using the concept of clustering. It turns out that the proposed approach has a significant compression ratio without a serious sacrifice of the visual quality of the model.