Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Hybrid Lighting for faster rendering of scenes with many lights

Hybrid Lighting for faster rendering of scenes with many lights There is growing interest in rendering scenes with many lights, where scenes typically contain hundreds to thousands of lights. Each light illuminates geometry within a finite extent called a light volume. A key aspect of performance is determining which lights apply to what geometry, and then applying those lights efficiently. We present a GPU-based approach using spatial data structures, binning lights by depth analytically while also taking advantage of hardware rasterization. This improves light binning performance by 3–6 $$\times $$ × . We also present a GPU memory and cache friendly data structure that takes two passes to build, giving 4–10 $$\times $$ × improved performance when applying lighting and an overall improvement of 1.3–4 $$\times $$ × for total frametime. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The Visual Computer Springer Journals

Hybrid Lighting for faster rendering of scenes with many lights

Loading next page...
 
/lp/springer_journal/hybrid-lighting-for-faster-rendering-of-scenes-with-many-lights-7vKXbmiQVl
Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer-Verlag GmbH Germany, part of Springer Nature
Subject
Computer Science; Computer Graphics; Computer Science, general; Artificial Intelligence (incl. Robotics); Image Processing and Computer Vision
ISSN
0178-2789
eISSN
1432-2315
DOI
10.1007/s00371-018-1535-5
Publisher site
See Article on Publisher Site

Abstract

There is growing interest in rendering scenes with many lights, where scenes typically contain hundreds to thousands of lights. Each light illuminates geometry within a finite extent called a light volume. A key aspect of performance is determining which lights apply to what geometry, and then applying those lights efficiently. We present a GPU-based approach using spatial data structures, binning lights by depth analytically while also taking advantage of hardware rasterization. This improves light binning performance by 3–6 $$\times $$ × . We also present a GPU memory and cache friendly data structure that takes two passes to build, giving 4–10 $$\times $$ × improved performance when applying lighting and an overall improvement of 1.3–4 $$\times $$ × for total frametime.

Journal

The Visual ComputerSpringer Journals

Published: May 2, 2018

References