Immersive Analytics of Multidimensional Volumetric Data

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Abstract

Understanding and interpreting volumetric multidimensional data is a complex and cognitively demanding task. Especially in the field of material science the exploration of large spatial data is crucial. Non-destructive testing (NDT) plays an essential role in industrial production, especially in the field of material and component testing, regarding the analysis, visualization, and optimization of new, highly complex material systems such as fiber composites. In order to support the increasing demands on these materials and components of the future in industrial applications, extensive inspections and controls are essential. NDT inspection data generated by imaging techniques such as X-ray computed tomography (XCT) include 2D images, volumetric models, and derived high-dimensional data spaces. They can rarely, or only to a limited extent, be evaluated on desktop monitors using standard 2D visualization techniques. Therefore, novel immersive visualization and interaction techniques using Virtual Reality (VR) were developed in this thesis to investigate highly complex, heterogeneous material systems. We present a novel technique called "Model in Miniature" for an effective and interactive exploration and visual analysis of fiber characteristics. Furthermore, we combine different approaches like exploded views, histograms, and node-link diagrams to provide unique insights into the composite materials. Using embodied interaction and navigation, and enhancing the user’s abilities, previously impossible insights into the most complex material structures are possible. We use the latest findings from the field of Immersive Analytics to make the spatial data more comprehensible and test the results in a qualitative study with domain experts. The evaluation of our techniques has shown positive results, which indicate the benefits of an immersive analysis of composite materials and the exploration of overall high-dimensional volumes. The insights gained therefore represent an important step towards the further development of future immersive analysis platforms.

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BibTeX

@mastersthesis{Gall2020,
  title =      "Immersive Analytics of Multidimensional Volumetric Data",
  author =     "Alexander Gall",
  year =       "2020",
  abstract =   "Understanding and interpreting volumetric multidimensional
               data is a complex and cognitively demanding task. Especially
               in the field of material science the exploration of large
               spatial data is crucial. Non-destructive testing (NDT) plays
               an essential role in industrial production, especially in
               the field of material and component testing, regarding the
               analysis, visualization, and optimization of new, highly
               complex material systems such as fiber composites. In order
               to support the increasing demands on these materials and
               components of the future in industrial applications,
               extensive inspections and controls are essential. NDT
               inspection data generated by imaging techniques such as
               X-ray computed tomography (XCT) include 2D images,
               volumetric models, and derived high-dimensional data spaces.
               They can rarely, or only to a limited extent, be evaluated
               on desktop monitors using standard 2D visualization
               techniques. Therefore, novel immersive visualization and
               interaction techniques using Virtual Reality (VR) were
               developed in this thesis to investigate highly complex,
               heterogeneous material systems. We present a novel technique
               called "Model in Miniature" for an effective and
               interactive exploration and visual analysis of fiber
               characteristics. Furthermore, we combine different
               approaches like exploded views, histograms, and node-link
               diagrams to provide unique insights into the composite
               materials. Using embodied interaction and navigation, and
               enhancing the user’s abilities, previously impossible
               insights into the most complex material structures are
               possible. We use the latest findings from the field of
               Immersive Analytics to make the spatial data more
               comprehensible and test the results in a qualitative study
               with domain experts. The evaluation of our techniques has
               shown positive results, which indicate the benefits of an
               immersive analysis of composite materials and the
               exploration of overall high-dimensional volumes. The
               insights gained therefore represent an important step
               towards the further development of future immersive analysis
               platforms.",
  month =      nov,
  address =    "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria",
  school =     "Research Unit of Computer Graphics, Institute of Visual
               Computing and Human-Centered Technology, Faculty of
               Informatics, TU Wien ",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2020/Gall2020/",
}