A Generation Method from Boundary Representation Model to Binary Voxel Data by Using GPU

Abstract

Boundary representation and spatial partitioning models are widely used in CG. Though boundary representation models require only a small amount of data, manipulating shapes with them is complicated. Spatial partitioning models, on the other hand, have a simple data structure, making shape manipulation easy. However, increasing the precision of the shape model requires ever more data. If these models can be transformed, good use can be made of the advantages of both models. To transform the boundary representation model into the voxel model it is necessary to decide whether each voxel is inside or outside of the shape being manipulated. However, this is a costly process. To solve this problem, we propose a fast method that generates a voxel model from a boundary representation model using GPU. We also describe a method for improving the accuracy of the voxel data.