Title: Tight Integration of Visual Analysis and 3D Real-Time Rendering
Language: English
Authors: Ortner, Thomas 
Qualification level: Doctoral
Advisor: Gröller, Eduard  
Issue Date: 2021
Number of Pages: 116
Qualification level: Doctoral
In domains, such as urban planning, civil engineering, or disaster management, analysts need to deal with geometric data that contain multivariate attributes. In addition to visual analysis of the attributes, tasks involve the understanding of shapes or judging spatial relations between geometric objects. Typical coordination of attribute and 3D views via brushing & linking reveals challenges.Brushed objects may be occluded or lie outside the current view, which leads to disorientation and the failing of spatial tasks. In this thesis we explore different approaches for a tight integration that addresses these challenges with respect to three application domains.First, we deal with the domain of tunnel inspection and documentation, concerned with revealing patterns in tunnel crack data. We integrate a 3D view with attribute views and present several domain-specific integration strategies. We derive a methodological framework that provides visualization designers with integration guidelines. Second, we explore the visual impact of buildings to a cityscape in the context of visibility-aware urban planning. We present the visualization solution Vis-A-Ware to qualitatively and quantitatively compare visibility data of buildings with respect to multiple viewpoints. Third, we are concerned with the geological analysis of digital outcrop models. Geologists manually summarize their analyses in 2D `correlation panels', which is time-consuming. With InCorr we provide users with a logging tool and an interactive correlation panel that evolves with the analysis.Our results demonstrate that the tight integration of geometric and attribute views is essential for certain domains and requires a methodological approach including thoughtful visualization and interaction design.
Keywords: Interactive Visualization; Integration Spatial and Non-Spatial Data Visualization; Methodology
URI: https://doi.org/10.34726/hss.2021.92046
DOI: 10.34726/hss.2021.92046
Library ID: AC16251330
Organisation: E193 - Institut für Visual Computing and Human-Centered Technology 
Publication Type: Thesis
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