Visualizing nD Point Clouds as Topological Landscape Profiles to Guide Local Data Analysis

Journal Article · Fri May 04 00:00:00 EDT 2012 · IEEE Transactions on Visualization and Computer Graphics

DOI:https://doi.org/10.1109/TVCG.2012.120· OSTI ID:1225632

Oesterling, Patrick ^[1]; Heine, Christian ^[2]; Weber, Gunther H. ^[3]; Scheuermann, Gerik ^[1]

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1. Univ. of Leipzig (Germany). Computer Science Dept.
2. Univ. of Leipzig (Germany). Computer Science Dept.; Federal Inst. of Technology (ETH), Zurich (Switzerland). Dept. of Computer Science
3. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division

Analyzing high-dimensional point clouds is a classical challenge in visual analytics. Traditional techniques, such as projections or axis-based techniques, suffer from projection artifacts, occlusion, and visual complexity.We propose to split data analysis into two parts to address these shortcomings. First, a structural overview phase abstracts data by its density distribution. This phase performs topological analysis to support accurate and non-overlapping presentation of the high-dimensional cluster structure as a topological landscape profile. Utilizing a landscape metaphor, it presents clusters and their nesting as hills whose height, width, and shape reflect cluster coherence, size, and stability, respectively. A second local analysis phase utilizes this global structural knowledge to select individual clusters or point sets for further, localized data analysis. Focusing on structural entities significantly reduces visual clutter in established geometric visualizations and permits a clearer, more thorough data analysis. In conclusion, this analysis complements the global topological perspective and enables the user to study subspaces or geometric properties, such as shape.

• Research Organization: Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR); German Science Foundation (DFG)
• DOE Contract Number: AC02-05CH11231; SCHE663/4-1
• OSTI ID: 1225632
• Report Number(s): LBNL-5694E
• Journal Information: IEEE Transactions on Visualization and Computer Graphics, Vol. 19, Issue 3; ISSN 1077-2626
• Publisher: IEEE
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICS AND COMPUTING
visual metaphors
Point clouds
high-dimensional data
cluster analysis
dimension reduction
scalar topology
Visualization
Vegetation
Data visualization
Shape
Density functional theory
Image color analysis
Topology