5D Covariance Tracing for Efficient Defocus and Motion Blur

Laurent Belcour, Cyril Soler, Nicolas Holzschuch, Fredo Durand, Katric Subr

Research output: Contribution to journalArticle

38 Citations (Scopus)

Abstract

The rendering of effects such as motion blur and depth-of-field requires costly 5D integrals. We accelerate their computation through adaptive sampling and reconstruction based on the prediction of the anisotropy and bandwidth of the integrand. For this, we develop a new frequency analysis of the 5D temporal light-field, and show that first-order motion can be handled through simple changes of coordinates in 5D. We further introduce a compact representation of the spectrum using the covariance matrix and Gaussian approximations. We derive update equations for the 5 x 5 covariance matrices for each atomic light transport event, such as transport, occlusion, BRDF, texture, lens, and motion. The focus on atomic operations makes our work general, and removes the need for special-case formulas. We present a new rendering algorithm that computes 5D covariance matrices on the image plane by tracing paths through the scene, focusing on the single-bounce case. This allows us to reduce sampling rates when appropriate and perform reconstruction of images with complex depth-of-field and motion blur effects.

Original languageEnglish
Article number31
Number of pages18
JournalACM Transactions on Graphics
Volume32
Issue number3
DOIs
Publication statusPublished - Jun 2013

Keywords

  • Theory
  • Performance
  • global illumination
  • Fourier analysis
  • motion blur
  • GLOBAL ILLUMINATION
  • FREQUENCY-ANALYSIS
  • COMPUTER-GRAPHICS
  • LIGHT TRANSPORT
  • DEPTH
  • DIFFERENTIALS
  • COMPONENTS

Cite this