Photo-Guided Exploration of Volume Data Features (Unknown language)

How to get this document?

Download
Commercial Copyright fee: €14.50 Basic fee: €4.00 Total price: €18.50
Academic Copyright fee: €4.50 Basic fee: €2.00 Total price: €6.50

In this work, we pose the question of whether, by considering qualitative information such as a sample target image as input, one can produce a rendered image of scientific data that is similar to the target. The algorithm resulting from our research allows one to ask the question of whether features like those in the target image exists in a given dataset. In that way, our method is one of imagery query or reverse engineering, as opposed to manual parameter tweaking of the full visualization pipeline. For target images, we can use real-world photographs of physical phenomena. Our method leverages deep neural networks and evolutionary optimization. Using a trained similarity function that measures the difference between renderings of a phenomenon and real-world photographs, our method optimizes rendering parameters. We demonstrate the efficacy of our method using a superstorm simulation dataset and images found online. We also discuss a parallel implementation of our method, which was run on NCSA's Blue Waters.

Table of contents conference proceedings

The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.

1
PaViz: A Power-Adaptive Framework for Optimizing Visualization Performance
Labasan, Stephanie / Larsen, Matthew / Childs, Hank / Rountree, Barry | 2017
11
Prediction of Distributed Volume Visualization Performance to Support Render Hardware Acquisition
Tkachev, Gleb / Frey, Steffen / Müller, Christoph / Bruder, Valentin / Ertl, Thomas | 2017
21
Progressive CPU Volume Rendering with Sample Accumulation
Usher, Will / Amstutz, Jefferson / Brownlee, Carson / Knoll, Aaron / Wald, Ingo | 2017
31
Photo-Guided Exploration of Volume Data Features
Raji, Mohammad / Hota, Alok / Sisneros, Robert / Messmer, Peter / Huang, Jian | 2017
41
A Space-Efficient Method for Navigable Ensemble Analysis and Visualization
Hota, Alok / Raji, Mohammad / Hobson, Tanner / Huang, Jian | 2017
53
Interactive Exploration of Dissipation Element Geometry
Vierjahn, Tom / Schnorr, Andrea / Weyers, Benjamin / Denker, Dominik / Wald, Ingo / Garth, Christoph / Kuhlen, Torsten W. / Hentschel, Bernd | 2017
63
A Task-Based Parallel Rendering Component For Large-Scale Visualization Applications
Biedert, Tim / Werner, Kilian / Hentschel, Bernd / Garth, Christoph | 2017
73
Achieving Portable Performance For Wavelet Compression Using Data Parallel Primitives
Li, Shaomeng / Marsaglia, Nicole / Chen, Vincent / Sewell, Christopher / Clyne, John / Childs, Hank | 2017