An Adaptive Point Sampler on a Regular Latice

Abdalla G.M. Ahmed, Till Niese, Hui Huang, Oliver Deussen

Research output: Contribution to conferencePaperpeer-review

23 Scopus citations

Abstract

We present a framework to distribute point samples with controlled spectral properties using a regular lattice of tiles with a single sample per tile. We employ a word-based identification scheme to identify individual tiles in the lattice. Our scheme is recursive, permitting tiles to be subdivided into smaller tiles that use the same set of IDs. The corresponding framework offers a very simple setup for optimization towards different spectral properties. Small lookup tables are suficient to store all the information needed to produce different point sets. For blue noise with varying densities, we employ the bit-reversal principle to recursively traverse sub-tiles. Our framework is also capable of delivering multi-class blue noise samples. It is well-suited for different sampling scenarios in rendering, including area-light sampling (uniform and adaptive), and importance sampling. Other applications include stippling and distributing objects.

Original languageEnglish (US)
DOIs
StatePublished - 2017
EventACM SIGGRAPH 2017 - Los Angeles, United States
Duration: Jul 30 2017Aug 3 2017

Conference

ConferenceACM SIGGRAPH 2017
Country/TerritoryUnited States
CityLos Angeles
Period07/30/1708/3/17

Bibliographical note

Funding Information:
We thank the anonymous reviewers for their detailed feedback to improve the paper. Thanks to Cengiz Öztireli for sharing the grid test scene. Thanks to Carla Avo-lio for the voice over of the supporting video clip. Corresponding author is Ab-dalla G. M. Ahmed, abdalla_gafar@hotmail.com. This work was partially funded by Deutsche Forschungsgemeinschaft Grant (DE-620/22-1), the National Foreign 1000 Talent Plan (WQ201344000169), Leading Talents of Guangdong Program (00201509), NSFC (61522213, 61379090, 61232011), Guangdong Science and Technology Program (2015A030312015), and Shenzhen Innovation Program (JCYJ20151015151249564). Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. © 2017 Copyright held by the owner/author(s). Publication rights licensed to ACM. 0730-0301/2017/7-ART138 $15.00 DOI: http://dx.doi.org/10.1145/3072959.3073588

Publisher Copyright:
© 2017 Copyright held by the owner/author(s).

Keywords

  • Blue noise
  • Monte Carlo
  • Multi-class blue noise
  • Quasi-Monte Carlo
  • Sampling
  • Self-similarity
  • Thue-Morse word
  • Tiling

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design

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