LOCALIS: Locally-adaptive Line Simplification for GPU-based Geographic Vector Data Visualization

dc.contributor.authorAmiraghdam, Alirezaen_US
dc.contributor.authorDiehl, Alexandraen_US
dc.contributor.authorPajarola, Renatoen_US
dc.contributor.editorViola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatianaen_US
dc.date.accessioned2020-05-24T13:01:24Z
dc.date.available2020-05-24T13:01:24Z
dc.date.issued2020
dc.description.abstractVisualization of large vector line data is a core task in geographic and cartographic systems. Vector maps are often displayed at different cartographic generalization levels, traditionally by using several discrete levels-of-detail (LODs). This limits the generalization levels to a fixed and predefined set of LODs, and generally does not support smooth LOD transitions. However, fast GPUs and novel line rendering techniques can be exploited to integrate dynamic vector map LOD management into GPU-based algorithms for locally-adaptive line simplification and real-time rendering. We propose a new technique that interactively visualizes large line vector datasets at variable LODs. It is based on the Douglas-Peucker line simplification principle, generating an exhaustive set of line segments whose specific subsets represent the lines at any variable LOD. At run time, an appropriate and view-dependent error metric supports screen-space adaptive LOD levels and the display of the correct subset of line segments accordingly. Our implementation shows that we can simplify and display large line datasets interactively. We can successfully apply line style patterns, dynamic LOD selection lenses, and anti-aliasing techniques to our line rendering.en_US
dc.description.number3
dc.description.sectionheadersSpace and Time
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume39
dc.identifier.doi10.1111/cgf.13993
dc.identifier.issn1467-8659
dc.identifier.pages443-453
dc.identifier.urihttps://doi.org/10.1111/cgf.13993
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13993
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/]
dc.subjectHuman centered computing
dc.subjectGeographic visualization
dc.subjectVisualization techniques
dc.subjectTheory of computation
dc.subjectComputational geometry
dc.subjectComputing methodologies
dc.subjectRendering
dc.subjectRasterization
dc.titleLOCALIS: Locally-adaptive Line Simplification for GPU-based Geographic Vector Data Visualizationen_US
Files
Original bundle
Now showing 1 - 2 of 2
Loading...
Thumbnail Image
Name:
v39i3pp443-453.pdf
Size:
24.38 MB
Format:
Adobe Portable Document Format
No Thumbnail Available
Name:
1091-file1.mp4
Size:
203.21 MB
Format:
Unknown data format
Collections