Publikation: Empirical evaluation of no-reference VQA methods on a natural video quality database
Lade...
Dateien
Datum
2017
Autor:innen
Herausgeber:innen
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
URI (zitierfähiger Link)
DOI (zitierfähiger Link)
Internationale Patentnummer
Link zur Lizenz
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Open Access Green
Core Facility der Universität Konstanz
Titel in einer weiteren Sprache
Publikationstyp
Beitrag zu einem Konferenzband
Publikationsstatus
Published
Erschienen in
2017 Ninth International Conference on Quality of Multimedia Experience (QoMEX), May 29 - June 2, 2017, Erfurt, Germany, Proceedings. Piscataway, NJ: IEEE, 2017, 17011019. eISSN 2472-7814. ISBN 978-1-5386-4024-1. Available under: doi: 10.1109/QoMEX.2017.7965644
Zusammenfassung
No-Reference (NR) Video Quality Assessment (VQA) is a challenging task since it predicts the visual quality of a video sequence without comparison to some original reference video. Several NR-VQA methods have been proposed. However, all of them were designed and tested on databases with artificially distorted videos. Therefore, it remained an open question how well these NR-VQA methods perform for natural videos. We evaluated two popular VQA methods on our newly built natural VQA database KoNViD-1k. In addition, we found that merely combining five simple VQA-related features, i.e., contrast, colorfulness, blurriness, spatial information, and temporal information, already gave a performance about as well as those of the established NR-VQA methods. However, for all methods we found that they are unsatisfying when assessing natural videos (correlation coefficients below 0.6). These findings show that NR-VQA is not yet matured and in need of further substantial improvement.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
Schlagwörter
empirical evaluation, no-reference, video quality assessment, feature combination
Konferenz
2017 Ninth International Conference on Quality of Multimedia Experience (QoMEX), 31. Mai 2017 - 2. Juni 2017, Erfurt, Germany
Rezension
undefined / . - undefined, undefined
Zitieren
ISO 690
MEN, Hui, Hanhe LIN, Dietmar SAUPE, 2017. Empirical evaluation of no-reference VQA methods on a natural video quality database. 2017 Ninth International Conference on Quality of Multimedia Experience (QoMEX). Erfurt, Germany, 31. Mai 2017 - 2. Juni 2017. In: 2017 Ninth International Conference on Quality of Multimedia Experience (QoMEX), May 29 - June 2, 2017, Erfurt, Germany, Proceedings. Piscataway, NJ: IEEE, 2017, 17011019. eISSN 2472-7814. ISBN 978-1-5386-4024-1. Available under: doi: 10.1109/QoMEX.2017.7965644BibTex
@inproceedings{Men2017-05Empir-41343,
year={2017},
doi={10.1109/QoMEX.2017.7965644},
title={Empirical evaluation of no-reference VQA methods on a natural video quality database},
isbn={978-1-5386-4024-1},
publisher={IEEE},
address={Piscataway, NJ},
booktitle={2017 Ninth International Conference on Quality of Multimedia Experience (QoMEX), May 29 - June 2, 2017, Erfurt, Germany, Proceedings},
author={Men, Hui and Lin, Hanhe and Saupe, Dietmar},
note={Article Number: 17011019}
}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/123456789/41343">
<dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2018-02-14T10:55:51Z</dc:date>
<dc:contributor>Men, Hui</dc:contributor>
<dc:language>eng</dc:language>
<dc:creator>Lin, Hanhe</dc:creator>
<dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/41343/1/Men_2-6ozepo9wxupa0.pdf"/>
<dc:creator>Men, Hui</dc:creator>
<foaf:homepage rdf:resource="http://localhost:8080/"/>
<dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
<dc:contributor>Lin, Hanhe</dc:contributor>
<dcterms:issued>2017-05</dcterms:issued>
<dcterms:title>Empirical evaluation of no-reference VQA methods on a natural video quality database</dcterms:title>
<bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/41343"/>
<dcterms:abstract xml:lang="eng">No-Reference (NR) Video Quality Assessment (VQA) is a challenging task since it predicts the visual quality of a video sequence without comparison to some original reference video. Several NR-VQA methods have been proposed. However, all of them were designed and tested on databases with artificially distorted videos. Therefore, it remained an open question how well these NR-VQA methods perform for natural videos. We evaluated two popular VQA methods on our newly built natural VQA database KoNViD-1k. In addition, we found that merely combining five simple VQA-related features, i.e., contrast, colorfulness, blurriness, spatial information, and temporal information, already gave a performance about as well as those of the established NR-VQA methods. However, for all methods we found that they are unsatisfying when assessing natural videos (correlation coefficients below 0.6). These findings show that NR-VQA is not yet matured and in need of further substantial improvement.</dcterms:abstract>
<dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
<dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/41343/1/Men_2-6ozepo9wxupa0.pdf"/>
<dc:creator>Saupe, Dietmar</dc:creator>
<dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
<dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2018-02-14T10:55:51Z</dcterms:available>
<dc:rights>terms-of-use</dc:rights>
<void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
<dc:contributor>Saupe, Dietmar</dc:contributor>
</rdf:Description>
</rdf:RDF>Interner Vermerk
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
Prüfungsdatum der Dissertation
Finanzierungsart
Kommentar zur Publikation
Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Ja
