Visualization of Multivariate Data on Surfaces

  • Allan Rocha UCalgary
  • Usman Alim UCalgary
  • Mario Costa Sousa UCalgary

Resumo


This research builds upon ideas introduced and discussed many years ago that focus on the problem of visualizing multiple attributes on surfaces in a single view. Here we present a new perspective to this problem as well as a solution that allows us to design, visualize and interact with multivariate data on surfaces. Building upon multidisciplinary aspects, we present a new way to visualize multivariate data on surfaces by exploiting the concept of layering. First, we introduce a new real-time rendering technique and the concept of Decal-Maps, which fills a gap in the literature and allow us to create 2D visual representations such as glyphs that follow the surface geometry. Building on this technique, we propose the layering framework to facilitate the multivariate visualization design on surfaces. The use of this concept and framework allows us to connect and generalize concepts established in flat space, such as 2D maps, to arbitrary surfaces. Decal-maps opens up other new possibilities such as the use of interaction techniques. Here we demonstrate this potential by introducing a new interaction technique that allows us to explore multivariate data and to create customized focus+context visualizations on surfaces. This is achieved by introducing a new category of lenses, Decal-Lenses, which extends the concept of magic-lenses from flat space to general surfaces. Finally, this thesis showcases the process of multivariate visual design and data exploration through a series of examples from several domains such as Medicine and Geology.

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Publicado
07/11/2020
ROCHA, Allan; ALIM, Usman; SOUSA, Mario Costa. Visualization of Multivariate Data on Surfaces. In: WORKSHOP DE TESES E DISSERTAÇÕES - CONFERENCE ON GRAPHICS, PATTERNS AND IMAGES (SIBGRAPI), 33. , 2020, Evento Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2020 . p. 133-138. DOI: https://doi.org/10.5753/sibgrapi.est.2020.12995.