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2014 IEEE 4th Symposium on Large Data Analysis and Visualization (LDAV) (2014)
Nov. 9, 2014 to Nov. 10, 2014
ISBN: 978-1-4799-5215-1
pp: 59-65
Oliver Fernandes , University of Stuttgart, Germany
Steffen Frey , University of Stuttgart, Germany
Filip Sadlo , University of Stuttgart, Germany
Thomas Ertl , University of Stuttgart, Germany
Volumetric depth images (VDI) are a view-dependent representation that combines the high quality of images with the explorability of 3D fields. By compressing the scalar data along view rays into sets of coherent supersegments, VDIs provide an efficient representation that supports a-posteriori changes of camera parameters. In this paper, we introduce space-time VDIs that achieve the data reduction that is required for efficient in-situ visualization, while still maintaining spatiotemporal flexibility. We provide an efficient space-time representation of VDI streams by exploiting inter-ray and inter-frame coherence, and introduce delta encoding for further data reduction. Our space-time VDI approach exhibits small computational overhead, is easy to integrate into existing simulation environments, and may help pave the way toward exascale computing.
Data visualization, Image color analysis, Encoding, Computational modeling, Rendering (computer graphics), Data models, Cameras

O. Fernandes, S. Frey, F. Sadlo and T. Ertl, "Space-time volumetric depth images for in-situ visualization," 2014 IEEE 4th Symposium on Large Data Analysis and Visualization (LDAV), France, 2014, pp. 59-65.
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