Immersive Visualizations of 3-dimensional scientific data pose unique interaction challenges. One challenge is to be able to interact with the visual volumetric representations of data using direct manipulation in a way that facilitates exploration and discovery, yet maintains data relationships. In this paper, we present Body-Prop Interaction, a novel tangible multimodal interface for immersive visualizations. Our interaction technique combines multiple input and output modalities with 3D printed open discs that are tracked and augmented with virtual information. To demonstrate our technique, we implemented interactive tasks for a volume visualization of graphite billet data. While demonstrated for this type of data visualization, our novel interaction technique has the potential to be used to interact with other types of augmented and virtual reality.

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.

eigifp is a MATLAB program for computing a few extreme eigenvalues and eigenvectors of the large symmetric generalized eigenvalue problem Ax = λ Bx . It is a black-box implementation of an inverse free preconditioned Krylov subspace projection method developed by Golub and Ye [2002]. It has important features that allow it to solve some difficult problems without any input from users. It is particularly suitable for problems where preconditioning by the standard shift-and-invert transformation is not feasible.