Using Entropy Impurity for Improved 3D Object Similarity Search

Lade...
Vorschaubild
Dateien
ICME04.pdf
ICME04.pdfGröße: 266.28 KBDownloads: 389
Datum
2004
Autor:innen
Bustos Cárdenas, Benjamin Eugenio
Vranić, Dejan V.
Herausgeber:innen
Kontakt
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
ArXiv-ID
Internationale Patentnummer
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Open Access Green
Core Facility der Universität Konstanz
Gesperrt bis
Titel in einer weiteren Sprache
Forschungsvorhaben
Organisationseinheiten
Zeitschriftenheft
Publikationstyp
Beitrag zu einem Konferenzband
Publikationsstatus
Published
Erschienen in
2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763). IEEE, 2004, pp. 1303-1306. ISBN 0-7803-8603-5. Available under: doi: 10.1109/ICME.2004.1394465
Zusammenfassung

Similarity search in 3D object databases is becoming an important problem in multimedia retrieval, with many practical applications. We investigate methods for improving the effectiveness in a retrieval system that implements multiple feature extraction algorithms to choose from. Our techniques are based on the entropy impurity measure, widely used in the context of decision trees. We propose a method for the a priori estimation of individual feature vector performance given a query. We then define two approaches that use this estimator to improve the retrieval effectiveness. Our experimental results show that significant improvements are achievable using these methods.

Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
Schlagwörter
Konferenz
2004 IEEE International Conference on Multimedia and Expo (ICME), Taipei, Taiwan
Rezension
undefined / . - undefined, undefined
Zitieren
ISO 690BUSTOS CÁRDENAS, Benjamin Eugenio, Daniel A. KEIM, Dietmar SAUPE, Tobias SCHRECK, Dejan V. VRANIĆ, 2004. Using Entropy Impurity for Improved 3D Object Similarity Search. 2004 IEEE International Conference on Multimedia and Expo (ICME). Taipei, Taiwan. In: 2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763). IEEE, 2004, pp. 1303-1306. ISBN 0-7803-8603-5. Available under: doi: 10.1109/ICME.2004.1394465
BibTex
@inproceedings{BustosCardenas2004Using-5418,
  year={2004},
  doi={10.1109/ICME.2004.1394465},
  title={Using Entropy Impurity for Improved 3D Object Similarity Search},
  isbn={0-7803-8603-5},
  publisher={IEEE},
  booktitle={2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763)},
  pages={1303--1306},
  author={Bustos Cárdenas, Benjamin Eugenio and Keim, Daniel A. and Saupe, Dietmar and Schreck, Tobias and Vranić, Dejan V.}
}
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/123456789/5418">
    <dc:contributor>Vranić, Dejan V.</dc:contributor>
    <dcterms:issued>2004</dcterms:issued>
    <dcterms:rights rdf:resource="http://creativecommons.org/licenses/by-nc-nd/2.0/"/>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-24T15:55:13Z</dcterms:available>
    <dc:creator>Bustos Cárdenas, Benjamin Eugenio</dc:creator>
    <dc:creator>Saupe, Dietmar</dc:creator>
    <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/5418"/>
    <dcterms:abstract xml:lang="eng">Similarity search in 3D object databases is becoming an important problem in multimedia retrieval, with many practical applications. We investigate methods for improving the effectiveness in a retrieval system that implements multiple feature extraction algorithms to choose from. Our techniques are based on the entropy impurity measure, widely used in the context of decision trees. We propose a method for the a priori estimation of individual feature vector performance given a query. We then define two approaches that use this estimator to improve the retrieval effectiveness. Our experimental results show that significant improvements are achievable using these methods.</dcterms:abstract>
    <dc:creator>Vranić, Dejan V.</dc:creator>
    <dc:contributor>Bustos Cárdenas, Benjamin Eugenio</dc:contributor>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-24T15:55:13Z</dc:date>
    <dcterms:bibliographicCitation>First publ. in: Proc. IEEE International Conference on Multimedia and Expo (ICME'04), 2004, vol. 2, pp. 1303-1306</dcterms:bibliographicCitation>
    <dc:contributor>Saupe, Dietmar</dc:contributor>
    <dc:creator>Schreck, Tobias</dc:creator>
    <dcterms:title>Using Entropy Impurity for Improved 3D Object Similarity Search</dcterms:title>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/5418/1/ICME04.pdf"/>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:language>eng</dc:language>
    <dc:contributor>Keim, Daniel A.</dc:contributor>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/5418/1/ICME04.pdf"/>
    <dc:format>application/pdf</dc:format>
    <dc:rights>Attribution-NonCommercial-NoDerivs 2.0 Generic</dc:rights>
    <dc:creator>Keim, Daniel A.</dc:creator>
    <dc:contributor>Schreck, Tobias</dc:contributor>
  </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