This preview shows pages 1–18. Sign up to view the full content.
This preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full Document
Unformatted text preview: Global Illumination CS 455 Objectives Compare and contrast local and global illumination Compare and contrast several approaches to global illumination Path tracing Radiosity Monte Carlo methods Appreciate the complexity of light. Global vs Local Illumination Cohab Canyon, Capitol Reef NP, Utah Cohab Canyon, Capitol Reef NP, Utah Path Tracing An extension to ray tracing Simulates global illumination Can handle all possible light bounces L(SD)*E (this is a reg exp, not a product) Introduced by Kajiya as a solution to the rendering equation Stochastically samples all light paths Handles area light sources, diffuse reflections Path Tracing Algorithms Determine the intensity of each pixel by tracing light transport paths Paths that start at light sources and carry energy A path of length k is a sequence of vertices <x0, , xk1> where every xi and xi+1 is mutually visible and x0 is on a light Important Paths We are most interested in the important paths Paths that go from a light source to the eye Paths that carry the most energy The rendering equation can be written as a sum of integrals, each one integrating over a different path length Nave Path Tracing (version 1) Start at a light Build a path by randomly choosing a direction at each bounce, send the ray in that direction, and add the point hit to the path vertex list Join the last point to the eye Problems? What path is achieved by this approach? Nave Path Tracing (version 2) Start at eye Build a path by randomly choosing a direction at each bounce, follow the path in that direction, add the point hit to the path vertex list Optionally join the last point to a light Problems? What paths are generated? Path Tracing (Kajiya) Start at eye At each bounce, send a ray out in the direction determined according to some distribution At each point on the path, cast a shadow ray and add direct lighting contribution at that point Send multiple paths per pixel, average the contributions to get the final intensity Path Tracing (Kajiya) Sampling Strategies The way in which the direction of each bounce is determined makes a big difference in image quality. Stratified Sampling Break the possible directions into subregions and cast one sample per subregion. Importance Sampling Sample according to the BRDF Send a ray through a pixel Trace the ray to its first intersected object From the intersected object, send out One ray to each light source One additional ray a diffusely reflected ray, a specularly reflected ray, or a transmissive ray Path Tracing Algorithm Selecting the ray to trace How do we select which ray to trace?...
View
Full
Document
 Winter '08
 Jones,M

Click to edit the document details