Stable Visual Summaries for Trajectory Collections

Lade...
Vorschaubild
Dateien
Zu diesem Dokument gibt es keine Dateien.
Datum
2021
Autor:innen
Wulms, Jules
Meulemans, Wouter
Verbeek, Kevin
Speckmann, Bettina
Herausgeber:innen
Kontakt
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
URI (zitierfähiger Link)
ArXiv-ID
Internationale Patentnummer
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Core Facility der Universität Konstanz
Gesperrt bis
Titel in einer weiteren Sprache
Publikationstyp
Beitrag zu einem Konferenzband
Publikationsstatus
Published
Erschienen in
Proceedings : 2021 IEEE 14th Pacific Visualization Symposium : PacificVis 2021. Piscataway, NJ: IEEE, 2021, pp. 61-70. ISSN 2165-8765. eISSN 2165-8773. ISBN 978-1-66543-931-2. Available under: doi: 10.1109/PacificVis52677.2021.00016
Zusammenfassung

The availability of devices that track moving objects has led to an explosive growth in trajectory data. When exploring the resulting large trajectory collections, visual summaries are a useful tool to identify time intervals of interest. A typical approach is to represent the spatial positions of the tracked objects at each time step via a one-dimensional ordering; visualizations of such orderings can then be placed in temporal order along a time line. There are two main criteria to assess the quality of the resulting visual summary: spatial quality - how well does the ordering capture the structure of the data at each time step, and stability - how coherent are the orderings over consecutive time steps or temporal ranges?In this paper we introduce a new Stable Principal Component (SPC) method to compute such orderings, which is explicitly parameterized for stability, allowing a trade-off between the spatial quality and stability. We conduct extensive computational experiments that quantitatively compare the orderings produced by ours and other stable dimensionality-reduction methods to various state-of-the-art approaches using a set of well-established quality metrics that capture spatial quality and stability. We conclude that stable dimensionality reduction outperforms existing methods on stability, without sacrificing spatial quality or efficiency; in particular, our new SPC method does so at a fraction of the computational costs.

Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
Schlagwörter
Konferenz
2021 IEEE 14th Pacific Visualization Symposium : PacificVis 2021 (online), 19. Apr. 2021 - 22. Apr. 2021
Rezension
undefined / . - undefined, undefined
Forschungsvorhaben
Organisationseinheiten
Zeitschriftenheft
Datensätze
Zitieren
ISO 690WULMS, Jules, Juri F. BUCHMÜLLER, Wouter MEULEMANS, Kevin VERBEEK, Bettina SPECKMANN, 2021. Stable Visual Summaries for Trajectory Collections. 2021 IEEE 14th Pacific Visualization Symposium : PacificVis 2021 (online), 19. Apr. 2021 - 22. Apr. 2021. In: Proceedings : 2021 IEEE 14th Pacific Visualization Symposium : PacificVis 2021. Piscataway, NJ: IEEE, 2021, pp. 61-70. ISSN 2165-8765. eISSN 2165-8773. ISBN 978-1-66543-931-2. Available under: doi: 10.1109/PacificVis52677.2021.00016
BibTex
@inproceedings{Wulms2021Stabl-54529,
  year={2021},
  doi={10.1109/PacificVis52677.2021.00016},
  title={Stable Visual Summaries for Trajectory Collections},
  isbn={978-1-66543-931-2},
  issn={2165-8765},
  publisher={IEEE},
  address={Piscataway, NJ},
  booktitle={Proceedings : 2021 IEEE 14th Pacific Visualization Symposium : PacificVis 2021},
  pages={61--70},
  author={Wulms, Jules and Buchmüller, Juri F. and Meulemans, Wouter and Verbeek, Kevin and Speckmann, Bettina}
}
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/123456789/54529">
    <dc:rights>terms-of-use</dc:rights>
    <dcterms:issued>2021</dcterms:issued>
    <dc:creator>Buchmüller, Juri F.</dc:creator>
    <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
    <dc:contributor>Speckmann, Bettina</dc:contributor>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2021-08-10T11:57:45Z</dcterms:available>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dc:creator>Wulms, Jules</dc:creator>
    <dcterms:title>Stable Visual Summaries for Trajectory Collections</dcterms:title>
    <dcterms:abstract xml:lang="eng">The availability of devices that track moving objects has led to an explosive growth in trajectory data. When exploring the resulting large trajectory collections, visual summaries are a useful tool to identify time intervals of interest. A typical approach is to represent the spatial positions of the tracked objects at each time step via a one-dimensional ordering; visualizations of such orderings can then be placed in temporal order along a time line. There are two main criteria to assess the quality of the resulting visual summary: spatial quality - how well does the ordering capture the structure of the data at each time step, and stability - how coherent are the orderings over consecutive time steps or temporal ranges?In this paper we introduce a new Stable Principal Component (SPC) method to compute such orderings, which is explicitly parameterized for stability, allowing a trade-off between the spatial quality and stability. We conduct extensive computational experiments that quantitatively compare the orderings produced by ours and other stable dimensionality-reduction methods to various state-of-the-art approaches using a set of well-established quality metrics that capture spatial quality and stability. We conclude that stable dimensionality reduction outperforms existing methods on stability, without sacrificing spatial quality or efficiency; in particular, our new SPC method does so at a fraction of the computational costs.</dcterms:abstract>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2021-08-10T11:57:45Z</dc:date>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/54529"/>
    <dc:creator>Meulemans, Wouter</dc:creator>
    <dc:contributor>Meulemans, Wouter</dc:contributor>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:language>eng</dc:language>
    <dc:contributor>Verbeek, Kevin</dc:contributor>
    <dc:creator>Verbeek, Kevin</dc:creator>
    <dc:contributor>Wulms, Jules</dc:contributor>
    <dc:contributor>Buchmüller, Juri F.</dc:contributor>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:creator>Speckmann, Bettina</dc:creator>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
  </rdf:Description>
</rdf:RDF>
Interner Vermerk
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
Kontakt
URL der Originalveröffentl.
Prüfdatum der URL
Prüfungsdatum der Dissertation
Finanzierungsart
Kommentar zur Publikation
Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Ja
Begutachtet
Diese Publikation teilen