Stochastic tomography and its applications in 3D imaging of mixing fluids

James Gregson*, Michael Krimerman, Matthias B. Hullin, Wolfgang Heidrich

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

56 Scopus citations

Abstract

We present a novel approach for highly detailed 3D imaging of turbulent fluid mixing behaviors. The method is based on visible light computed tomography, and is made possible by a new stochastic tomographic reconstruction algorithm based on random walks. We show that this new stochastic algorithm is competitive with specialized tomography solvers such as SART, but can also easily include arbitrary convex regularizers that make it possible to obtain highquality reconstructions with a very small number of views. Finally, we demonstrate that the same stochastic tomography approach can also be used to directly re-render arbitrary 2D projections without the need to ever store a 3D volume grid.

Original languageEnglish (US)
Article number52
JournalACM Transactions on Graphics
Volume31
Issue number4
DOIs
StatePublished - Jul 1 2012

Keywords

  • Fluid Imaging
  • Stochastic sampling
  • Tomography

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design

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