A Recursive Subdivision Technique for Sampling Multi-class Scatterplots
| dc.contributor.author | Chen, Xin | |
| dc.contributor.author | Ge, Tong | |
| dc.contributor.author | Zhang, Jian | |
| dc.contributor.author | Chen, Baoquan | |
| dc.contributor.author | Fu, Chi-Wing | |
| dc.contributor.author | Deussen, Oliver | |
| dc.contributor.author | Wang, Yunhai | |
| dc.date.accessioned | 2019-09-11T09:59:20Z | |
| dc.date.available | 2019-09-11T09:59:20Z | |
| dc.date.issued | 2020-01 | |
| dc.description.abstract | We present a non-uniform recursive sampling technique for multi-class scatterplots, with the specific goal of faithfully presenting relative data and class densities, while preserving major outliers in the plots. Our technique is based on a customized binary kd-tree, in which leaf nodes are created by recursively subdividing the underlying multi-class density map. By backtracking, we merge leaf nodes until they encompass points of all classes for our subsequently applied outlier-aware multi-class sampling strategy. A quantitative evaluation shows that our approach can better preserve outliers and at the same time relative densities in multi-class scatterplots compared to the previous approaches, several case studies demonstrate the effectiveness of our approach in exploring complex and real world data. | eng |
| dc.description.version | published | eng |
| dc.identifier.doi | 10.1109/TVCG.2019.2934541 | eng |
| dc.identifier.pmid | 31442987 | eng |
| dc.identifier.uri | https://kops.uni-konstanz.de/handle/123456789/46820 | |
| dc.language.iso | eng | eng |
| dc.subject.ddc | 004 | eng |
| dc.title | A Recursive Subdivision Technique for Sampling Multi-class Scatterplots | eng |
| dc.type | JOURNAL_ARTICLE | eng |
| dspace.entity.type | Publication | |
| kops.citation.bibtex | @article{Chen2020-01Recur-46820,
year={2020},
doi={10.1109/TVCG.2019.2934541},
title={A Recursive Subdivision Technique for Sampling Multi-class Scatterplots},
number={1},
volume={26},
issn={1077-2626},
journal={IEEE Transactions on Visualization and Computer Graphics},
pages={729--738},
author={Chen, Xin and Ge, Tong and Zhang, Jian and Chen, Baoquan and Fu, Chi-Wing and Deussen, Oliver and Wang, Yunhai}
} | |
| kops.citation.iso690 | CHEN, Xin, Tong GE, Jian ZHANG, Baoquan CHEN, Chi-Wing FU, Oliver DEUSSEN, Yunhai WANG, 2020. A Recursive Subdivision Technique for Sampling Multi-class Scatterplots. In: IEEE Transactions on Visualization and Computer Graphics. Institute of Electrical and Electronics Engineers (IEEE). 2020, 26(1), pp. 729-738. ISSN 1077-2626. eISSN 1941-0506. Available under: doi: 10.1109/TVCG.2019.2934541 | deu |
| kops.citation.iso690 | CHEN, Xin, Tong GE, Jian ZHANG, Baoquan CHEN, Chi-Wing FU, Oliver DEUSSEN, Yunhai WANG, 2020. A Recursive Subdivision Technique for Sampling Multi-class Scatterplots. In: IEEE Transactions on Visualization and Computer Graphics. Institute of Electrical and Electronics Engineers (IEEE). 2020, 26(1), pp. 729-738. ISSN 1077-2626. eISSN 1941-0506. Available under: doi: 10.1109/TVCG.2019.2934541 | eng |
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| kops.sourcefield.plain | IEEE Transactions on Visualization and Computer Graphics. Institute of Electrical and Electronics Engineers (IEEE). 2020, 26(1), pp. 729-738. ISSN 1077-2626. eISSN 1941-0506. Available under: doi: 10.1109/TVCG.2019.2934541 | eng |
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