Feature tracking in VR for cumulus cloud life-cycle studies

TLDR: This paper presents an approach that uses a combination of off-line preprocessing and interactive visualization in VR to simplify and speed up the identification of interesting features for further study.

Abstract: Feature tracking in large data sets is traditionally an off-line, batch processing operation while virtual reality typically focuses on highly interactive tasks and applications. This paper presents an approach that uses a combination of off-line preprocessing and interactive visualization in VR to simplify and speed up the identification of interesting features for further study. We couch the discussion in terms of our collaborative research on using virtual reality for cumulus cloud life-cycle studies, where selecting suitable clouds for study is simple for the skilled observer but difficult to formalize. The preprocessing involves identifying individual clouds within the data set through a 4D connected components algorithm, and then saving isosurface, bounding box, and volume information. This information is then interactively visualized in our VR Cloud Explorer with various tools and information displays to identify the most interesting clouds. In a small pilot study, reasonable performance, both in the preprocessing phase and the visualization phase, has been measured.