Density estimation optimizations for global illumination

Density Estimation on Delaunay Triangulations

Density Estimation is a very popular method to compute global illumination solutions in a complex virtual scene. After simulating the re ection paths of a large number of photons in the scene, the illumination at a surface point is approximated by estimating the density of photon hits in the point's surrounding. In this paper we describe a novel approach to compute such a density approximation ...

A New Approach of Density Estimation for Global Illumination

This paper presents a new approach to generate view-independent global illumination solution using kernel density estimation. Kernel density estimation allows smooth reconstruction of the radiance from hit points generated by shooting random walk or photon tracing. The advantage of this method is that an unbiased Monte-Carlo algorithm simulates light transport and that light reconstruction intr...

Advanced Density Estimation Techniques for Global Illumination

Improved Illumination Estimation for Photon Maps in Architectural Scenes

The photon map algorithm provides a number of advantages for fast global illumination algorithms. In order to calculate the illumination at each point in a scene, the photon density needs to be estimated. Standard estimation methods will have problems with typical architectural scenes, as walls and corners will lead to undesirable light and shadow leaks. We introduce a new method for estimating...

Adaptive density estimation using an orthogonal series for global illumination

In Monte-Carlo photon-tracing methods energy-carrying particles are traced in an environment to generate hit points on object surfaces for simulating global illumination. The surface illumination can be reconstructed from particle hit points by solving a density estimation problem using an orthogonal series. The appropriate number of terms of an orthogonal series used for approximating surface ...