Visual-assisted Outlier Preservation for Scatterplot Sampling

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Date
2023
Authors
Yang, Haiyan
Pajarola, Renato
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
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.
Description

CCS Concepts: Human-centered computing → Information visualization; Visualization techniques

        
@inproceedings{
10.2312:vmv.20231233
,
booktitle = {
Vision, Modeling, and Visualization
},
editor = {
Guthe, Michael
 and 
Grosch, Thorsten
},
title = {{
Visual-assisted Outlier Preservation for Scatterplot Sampling
}},
author = {
Yang, Haiyan
 and 
Pajarola, Renato
},
year = {
2023
},
publisher = {
The Eurographics Association
},
ISBN = {
978-3-03868-232-5
},
DOI = {
10.2312/vmv.20231233
}
}
Citation
URI
https://doi.org/10.2312/vmv.20231233
 https://diglib.eg.org:443/handle/10.2312/vmv20231233
Collections
VMV2023