We present a fast and memory efficient algorithm for generating Compact Precomputed Voxelized Shadows. By performing much of the common sub-tree merging before identical nodes are ever created, we improve construction times by several orders of magnitude for large data structures, and require much less working memory. To further improve performance, we suggest two new algorithms with which the remaining common sub-trees can be merged. We also propose a new set of rules for resolving undefined regions, which significantly reduces the final memory footprint of the already heavily compressed data structure. Additionally, we examine the feasibility of using CPVS for many local lights and present two improvements to the original algorithm that allow us to handle hundreds of lights with high-quality, filtered shadows at real-time frame rates.

Download full-text PDF

Source
http://dx.doi.org/10.1109/TVCG.2016.2539955DOI Listing

Publication Analysis

Top Keywords

voxelized shadows
8
fast memory-efficient
4
memory-efficient construction
4
construction voxelized
4
shadows fast
4
fast memory
4
memory efficient
4
efficient algorithm
4
algorithm generating
4
generating compact
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!