抄録
This paper describes a new data compression method for spatial partitioning representation which gives a higher data compression ratio than conventional methods. To obtain high data compression, we introduce the Network model, which performs fast geometric operations for spatial partitioning representation. The Network model represents a shape by using only voxels on the surfaces. These voxels connect with each other to make a network structure. The model compresses data simply for spatial partitioning representation and has a better compression ratio than the Octree model. Moreover, the proposed method can eliminate a large quantity of voxel from Network model. The resulting compression ratio is better than the three-dimensional runlength approach. Experimental results show that the method is effective for compressing data for spatial partitioning representation and achieves a high compression ratio.
