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| Type | Conference or Workshop Paper |
| Scope | Discipline-based scholarship |
| Published in Proceedings | Yes |
| Title | Visual-assisted Outlier Preservation for Scatterplot Sampling |
| Organization Unit | |
| Authors |
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| Presentation Type | paper |
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| ISBN | 978-3-03868-232-5 |
| Page Range | 115 - 121 |
| Event Title | VMV: Vision, Modeling, and Visualization |
| Event Type | conference |
| Event Location | Braunschweig |
| Event Start Date | September 27 - 2023 |
| Event End Date | September 29 - 2023 |
| Series Name | Vision, Modeling, and Visualization |
| Publisher | The Eurographics Association |
| Abstract Text | Scatterplot sampling has long been an efficient and effective way to resolve the overplotting issues commonly occurring in large-scale scatterplot visualization applications. However, it is challenging to preserve the existence of low-density points or outliers after sampling for a sub-sampling algorithm if, at the same time, faithfully representing the relative data densities is of importance. In this work, we propose to address this issue in a visual-assisted manner. While the whole dataset is sub-sampled, the density of the outliers is modeled and visually integrated into the final scatterplot together with the sub-sampled point data. We showcase the effectiveness of our proposed method in various cases and user studies. |
| Free access at | DOI |
| Digital Object Identifier | 10.2312/vmv.20231233 |
| Other Identification Number | merlin-id:24379 |
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| Keywords | visualization, sampling, scatterplots, outlier removal |