James Gregson, Michael Krimerman, Matthias B. Hullin, Wolfgang Heidrich: Stochastic Tomography and its Applications in 3D Imaging of Mixing Fluids. In: ACM Transactions on Graphics, Vol. 31 (4), 2012 (Proc. SIGGRAPH), to appear.

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 high-quality 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.

This video is distributed under a Creative Commons license, creativecommons.org/licenses/by/3.0/
Please attribute the work by citing our SIGGRAPH 2012 article.

Find the project website at: cs.ubc.ca/labs/imager/tr/2012/StochasticTomography/

j vimeo.com/40171658

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