Interactive Context-Preserving Color Highlighting for Multiclass Scatterplots

dc.contributor.authorLu, Kecheng
dc.contributor.authorReda, Khairi
dc.contributor.authorDeussen, Oliver
dc.contributor.authorWang, Yunhai
dc.date.accessioned2023-08-01T14:02:25Z
dc.date.available2023-08-01T14:02:25Z
dc.date.issued2023-04-19
dc.description.abstractColor is one of the main visual channels used for highlighting elements of interest in visualization. However, in multi-class scatterplots, color highlighting often comes at the expense of degraded color discriminability. In this paper, we argue for context-preserving highlighting during the interactive exploration of multi-class scatterplots to achieve desired pop-out effects, while maintaining good perceptual separability among all classes and consistent color mapping schemes under varying points of interest. We do this by first generating two contrastive color mapping schemes with large and small contrasts to the background. Both schemes maintain good perceptual separability among all classes and ensure that when colors from the two palettes are assigned to the same class, they have a high color consistency in color names. We then interactively combine these two schemes to create a dynamic color mapping for highlighting different points of interest. We demonstrate the effectiveness through crowd-sourced experiments and case studies.
dc.description.versionpublisheddeu
dc.identifier.doi10.1145/3544548.3580734
dc.identifier.ppn188709962X
dc.identifier.urihttps://kops.uni-konstanz.de/handle/123456789/67467
dc.language.isoeng
dc.subjectColor Palettes
dc.subjectHighlighting
dc.subjectMulti-Class Scatterplots
dc.subjectDiscriminability
dc.subject.ddc004
dc.titleInteractive Context-Preserving Color Highlighting for Multiclass Scatterplotseng
dc.typeINPROCEEDINGS
dspace.entity.typePublication
kops.citation.bibtex
@inproceedings{Lu2023-04-19Inter-67467,
  year={2023},
  doi={10.1145/3544548.3580734},
  title={Interactive Context-Preserving Color Highlighting for Multiclass Scatterplots},
  isbn={978-1-4503-9421-5},
  publisher={ACM},
  address={New York, NY},
  booktitle={Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems},
  editor={Schmidt, Albrecht and Väänänen, Kaisa and Goyal, Tesh},
  author={Lu, Kecheng and Reda, Khairi and Deussen, Oliver and Wang, Yunhai},
  note={Article Number: 823}
}
kops.citation.iso690LU, Kecheng, Khairi REDA, Oliver DEUSSEN, Yunhai WANG, 2023. Interactive Context-Preserving Color Highlighting for Multiclass Scatterplots. CHI '23: CHI Conference on Human Factors in Computing Systems. Hamburg, Germany, 23. Apr. 2023 - 28. Apr. 2023. In: SCHMIDT, Albrecht, ed., Kaisa VÄÄNÄNEN, ed., Tesh GOYAL, ed.. Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. New York, NY: ACM, 2023, 823. ISBN 978-1-4503-9421-5. Available under: doi: 10.1145/3544548.3580734deu
kops.citation.iso690LU, Kecheng, Khairi REDA, Oliver DEUSSEN, Yunhai WANG, 2023. Interactive Context-Preserving Color Highlighting for Multiclass Scatterplots. CHI '23: CHI Conference on Human Factors in Computing Systems. Hamburg, Germany, Apr 23, 2023 - Apr 28, 2023. In: SCHMIDT, Albrecht, ed., Kaisa VÄÄNÄNEN, ed., Tesh GOYAL, ed.. Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. New York, NY: ACM, 2023, 823. ISBN 978-1-4503-9421-5. Available under: doi: 10.1145/3544548.3580734eng
kops.citation.rdf
<rdf:RDF
    xmlns:dcterms="http://purl.org/dc/terms/"
    xmlns:dc="http://purl.org/dc/elements/1.1/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:bibo="http://purl.org/ontology/bibo/"
    xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
    xmlns:foaf="http://xmlns.com/foaf/0.1/"
    xmlns:void="http://rdfs.org/ns/void#"
    xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > 
  <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/67467">
    <dc:creator>Wang, Yunhai</dc:creator>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:contributor>Reda, Khairi</dc:contributor>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/67467/1/Lu_2-wyi6nnfudi2b8.pdf"/>
    <dc:language>eng</dc:language>
    <dc:creator>Deussen, Oliver</dc:creator>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:contributor>Lu, Kecheng</dc:contributor>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/67467/1/Lu_2-wyi6nnfudi2b8.pdf"/>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/67467"/>
    <dc:contributor>Deussen, Oliver</dc:contributor>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2023-08-01T14:02:25Z</dcterms:available>
    <dc:creator>Lu, Kecheng</dc:creator>
    <dcterms:issued>2023-04-19</dcterms:issued>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2023-08-01T14:02:25Z</dc:date>
    <dcterms:abstract>Color is one of the main visual channels used for highlighting elements of interest in visualization. However, in multi-class scatterplots, color highlighting often comes at the expense of degraded color discriminability. In this paper, we argue for context-preserving highlighting during the interactive exploration of multi-class scatterplots to achieve desired pop-out effects, while maintaining good perceptual separability among all classes and consistent color mapping schemes under varying points of interest. We do this by first generating two contrastive color mapping schemes with large and small contrasts to the background. Both schemes maintain good perceptual separability among all classes and ensure that when colors from the two palettes are assigned to the same class, they have a high color consistency in color names. We then interactively combine these two schemes to create a dynamic color mapping for highlighting different points of interest. We demonstrate the effectiveness through crowd-sourced experiments and case studies.</dcterms:abstract>
    <dc:contributor>Wang, Yunhai</dc:contributor>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:creator>Reda, Khairi</dc:creator>
    <dcterms:title>Interactive Context-Preserving Color Highlighting for Multiclass Scatterplots</dcterms:title>
  </rdf:Description>
</rdf:RDF>
kops.conferencefieldCHI '23: CHI Conference on Human Factors in Computing Systems, 23. Apr. 2023 - 28. Apr. 2023, Hamburg, Germanydeu
kops.date.conferenceEnd2023-04-28
kops.date.conferenceStart2023-04-23
kops.description.openAccessopenaccessgreen
kops.flag.knbibliographytrue
kops.identifier.nbnurn:nbn:de:bsz:352-2-wyi6nnfudi2b8
kops.location.conferenceHamburg, Germany
kops.sourcefieldSCHMIDT, Albrecht, ed., Kaisa VÄÄNÄNEN, ed., Tesh GOYAL, ed.. <i>Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems</i>. New York, NY: ACM, 2023, 823. ISBN 978-1-4503-9421-5. Available under: doi: 10.1145/3544548.3580734deu
kops.sourcefield.plainSCHMIDT, Albrecht, ed., Kaisa VÄÄNÄNEN, ed., Tesh GOYAL, ed.. Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. New York, NY: ACM, 2023, 823. ISBN 978-1-4503-9421-5. Available under: doi: 10.1145/3544548.3580734deu
kops.sourcefield.plainSCHMIDT, Albrecht, ed., Kaisa VÄÄNÄNEN, ed., Tesh GOYAL, ed.. Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. New York, NY: ACM, 2023, 823. ISBN 978-1-4503-9421-5. Available under: doi: 10.1145/3544548.3580734eng
kops.title.conferenceCHI '23: CHI Conference on Human Factors in Computing Systems
relation.isAuthorOfPublication4e85f041-bb89-4e27-b7d6-acd814feacb8
relation.isAuthorOfPublication.latestForDiscovery4e85f041-bb89-4e27-b7d6-acd814feacb8
source.bibliographicInfo.articleNumber823
source.contributor.editorSchmidt, Albrecht
source.contributor.editorVäänänen, Kaisa
source.contributor.editorGoyal, Tesh
source.identifier.isbn978-1-4503-9421-5
source.publisherACM
source.publisher.locationNew York, NY
source.titleProceedings of the 2023 CHI Conference on Human Factors in Computing Systems

Dateien

Originalbündel

Gerade angezeigt 1 - 1 von 1
Vorschaubild nicht verfügbar
Name:
Lu_2-wyi6nnfudi2b8.pdf
Größe:
3.45 MB
Format:
Adobe Portable Document Format
Lu_2-wyi6nnfudi2b8.pdf
Lu_2-wyi6nnfudi2b8.pdfGröße: 3.45 MBDownloads: 92