Particle density estimation for particle-based volume rendering

Application for the large irregular volume datasets

Abstract

In this paper, we describe a stochastic approach for previewing large irregular volume datasets with small memory resources. It is well known that the memory bandwidth consumed by visibility sorting becomes the limiting factor when carrying out volume rendering of large irregular volume datasets. To solve this problem, previous techniques without visibility sorting ignored absorption and emission in their optical models. Our technique represents a given irregular volume dataset as a set of opaque, emissive particles whose size is sufficiently small with respect to the pixel size. We applied our proposed technique to a volume composed of about 1G tetrahedral cells to confirm its effectiveness.