We introduce temporally unstructured volumes (TUVs), a data structure for representing 4D volume data that is spatially structured but temporally unstructured, and Reves, an algorithm for constructing those volumes. The data structure supports efficient rendering of motion blur effects in volumes, including sub-frame motion. Reves is a volumetric extension to the classic Reyes algorithm, and produces TUV data sets through spatio-temporal stochastic sampling. Our method scales linearly and maximizes data locality and parallelism both during construc- tion and rendering of volumes, making it suitable for ray tracing, and supports arbitrarily large input models. Compared to the current state-of-the-art in volumetric motion blur, our approach produces more accurate results using less memory and less time, and it can also provide high-quality re-timing of volumetric data sets, such as fluid simulations.
Efficient Rendering of Volumetric Motion Blur Using Temporally Unstructured Volumes
February 14, 2016