TY - GEN
T1 - Enhancements to VTK enabling scientific visualization in immersive environments
AU - O'leary, Patrick
AU - Jhaveri, Sankhesh
AU - Chaudhary, Aashish
AU - Sherman, William
AU - Martin, Ken
AU - Lonie, David
AU - Whiting, Eric
AU - Money, James
AU - McKenzie, Sandy
N1 - Funding Information:
The presented work was made possible due to support in part by funding from U.S. Department of Energy (Office of Nuclear Energy) Fast Track SBIR award DE-SC0010119, Dan Funk (program manager) and Idaho National Laboratory's Center for Advanced Energy Studies. Funding for embedding OpenVR, the OpenGL 3.2+ pipeline and SMP tools comes from the National Institutes of Health under the grant NIH R01EB014955 "Accelerating Community-Driven Medical Innovation with VTK."
Publisher Copyright:
© 2017 IEEE.
PY - 2017/4/4
Y1 - 2017/4/4
N2 - Modern scientific, engineering and medical computational simulations, as well as experimental and observational data sensing/measuring devices, produce enormous amounts of data. While statistical analysis provides insight into this data, scientific visualization is tactically important for scientific discovery, product design and data analysis. These benefits are impeded, however, when scientific visualization algorithms are implemented from scratch - a time-consuming and redundant process in immersive application development. This process can greatly benefit from leveraging the state-of-the-art open-source Visualization Toolkit (VTK) and its community. Over the past two (almost three) decades, integrating VTK with a virtual reality (VR) environment has only been attempted to varying degrees of success. In this paper, we demonstrate two new approaches to simplify this amalgamation of an immersive interface with visualization rendering from VTK. In addition, we cover several enhancements to VTK that provide near real-time updates and efficient interaction. Finally, we demonstrate the combination of VTK with both Vrui and OpenVR immersive environments in example applications.
AB - Modern scientific, engineering and medical computational simulations, as well as experimental and observational data sensing/measuring devices, produce enormous amounts of data. While statistical analysis provides insight into this data, scientific visualization is tactically important for scientific discovery, product design and data analysis. These benefits are impeded, however, when scientific visualization algorithms are implemented from scratch - a time-consuming and redundant process in immersive application development. This process can greatly benefit from leveraging the state-of-the-art open-source Visualization Toolkit (VTK) and its community. Over the past two (almost three) decades, integrating VTK with a virtual reality (VR) environment has only been attempted to varying degrees of success. In this paper, we demonstrate two new approaches to simplify this amalgamation of an immersive interface with visualization rendering from VTK. In addition, we cover several enhancements to VTK that provide near real-time updates and efficient interaction. Finally, we demonstrate the combination of VTK with both Vrui and OpenVR immersive environments in example applications.
KW - Immersive environments
KW - Scientific visualization
KW - Virtual reality
UR - https://www.scopus.com/pages/publications/85018407810
U2 - 10.1109/VR.2017.7892246
DO - 10.1109/VR.2017.7892246
M3 - Conference contribution
AN - SCOPUS:85018407810
T3 - Proceedings - IEEE Virtual Reality
SP - 186
EP - 194
BT - 2017 IEEE Virtual Reality, VR 2017 - Proceedings
PB - IEEE Computer Society
T2 - 19th IEEE Virtual Reality, VR 2017
Y2 - 18 March 2017 through 22 March 2017
ER -