Publikation:

Expertise screening in crowdsourcing image quality

Vorschaubild

Dateien

Zu diesem Dokument gibt es keine Dateien.

Datum

2018

Autor:innen

Herausgeber:innen

Kontakt

ISSN der Zeitschrift

Electronic ISSN

ISBN

Bibliografische Daten

Verlag

Schriftenreihe

Auflagebezeichnung

URI (zitierfähiger Link)
DOI (zitierfähiger Link)
https://doi.org/10.1109/QoMEX.2018.8463427
ArXiv-ID

Internationale Patentnummer

Angaben zur Forschungsförderung

Projekt

Open Access-Veröffentlichung

Sammlungen

Informatik und Informationswissenschaft: Publikationen
Core Facility der Universität Konstanz

Gesperrt bis

Titel in einer weiteren Sprache

Publikationstyp
Beitrag zu einem Konferenzband
Publikationsstatus
Published

Erschienen in

2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX). Piscataway, New Jersey, USA: IEEE, 2018, pp. 276-281. eISSN 2472-7814. ISBN 978-1-5386-2605-4. Available under: doi: 10.1109/QoMEX.2018.8463427

Zusammenfassung

We propose a screening approach to find reliable and effectively expert crowd workers in image quality assessment (IQA). Our method measures the users' ability to identify image degradations by using test questions, together with several relaxed reliability checks. We conduct multiple experiments, obtaining reproducible results with a high agreement between the expertise-screened crowd and the freelance experts of 0.95 Spearman rank order correlation (SROCC), with one restriction on the image type. Our contributions include a reliability screening method for uninformative users, a new type of test questions that rely on our proposed database 1 of pristine and artificially distorted images, a group agreement extrapolation method and an analysis of the crowdsourcing experiments.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
004 Informatik

Schlagwörter

Konferenz

2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX), 29. Mai 2018 - 1. Juni 2018, Cagliari, Italy
Rezension
undefined / . - undefined, undefined

Forschungsvorhaben

Organisationseinheiten

Zeitschriftenheft

Zugehörige Datensätze in KOPS

Zitieren

ISO 690HOSU, Vlad, Hanhe LIN, Dietmar SAUPE, 2018. Expertise screening in crowdsourcing image quality. 2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX). Cagliari, Italy, 29. Mai 2018 - 1. Juni 2018. In: 2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX). Piscataway, New Jersey, USA: IEEE, 2018, pp. 276-281. eISSN 2472-7814. ISBN 978-1-5386-2605-4. Available under: doi: 10.1109/QoMEX.2018.8463427
BibTex
@inproceedings{Hosu2018Exper-44631,
  year={2018},
  doi={10.1109/QoMEX.2018.8463427},
  title={Expertise screening in crowdsourcing image quality},
  isbn={978-1-5386-2605-4},
  publisher={IEEE},
  address={Piscataway, New Jersey, USA},
  booktitle={2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX)},
  pages={276--281},
  author={Hosu, Vlad and Lin, Hanhe and Saupe, Dietmar}
}
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/123456789/44631">
    <dcterms:issued>2018</dcterms:issued>
    <dc:creator>Hosu, Vlad</dc:creator>
    <dc:creator>Saupe, Dietmar</dc:creator>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2019-01-21T10:49:24Z</dc:date>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2019-01-21T10:49:24Z</dcterms:available>
    <dc:contributor>Hosu, Vlad</dc:contributor>
    <dcterms:abstract xml:lang="eng">We propose a screening approach to find reliable and effectively expert crowd workers in image quality assessment (IQA). Our method measures the users' ability to identify image degradations by using test questions, together with several relaxed reliability checks. We conduct multiple experiments, obtaining reproducible results with a high agreement between the expertise-screened crowd and the freelance experts of 0.95 Spearman rank order correlation (SROCC), with one restriction on the image type. Our contributions include a reliability screening method for uninformative users, a new type of test questions that rely on our proposed database&lt;sup&gt; 1&lt;/sup&gt; of pristine and artificially distorted images, a group agreement extrapolation method and an analysis of the crowdsourcing experiments.</dcterms:abstract>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dcterms:title>Expertise screening in crowdsourcing image quality</dcterms:title>
    <dc:language>eng</dc:language>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/44631"/>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:contributor>Saupe, Dietmar</dc:contributor>
    <dc:creator>Lin, Hanhe</dc:creator>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:contributor>Lin, Hanhe</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