Publikation:

Estimating 2D Multi-hand Poses from Single Depth Images

Lade...
Vorschaubild

Dateien

Duan_2-eag9rf9qwzit2.pdf
Duan_2-eag9rf9qwzit2.pdfGröße: 2.86 MBDownloads: 692

Datum

2019

Autor:innen

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

Publikationstyp
Beitrag zu einem Konferenzband
Publikationsstatus
Published

Erschienen in

LEAL-TAIXÉ, Laura, ed., Stefan ROTH, ed.. Computer Vision - ECCV 2018 Workshops : Munich, Germany, September 8-14, 2018, Proceedings, Part VI. Cham: Springer, 2019, pp. 257-272. Lecture Notes in Computer Science. 11134. ISSN 0302-9743. eISSN 1611-3349. ISBN 978-3-030-11023-9. Available under: doi: 10.1007/978-3-030-11024-6_17

Zusammenfassung

We present a novel framework based on Pictorial Structure (PS) models to estimate 2D multi-hand poses from depth images. Most existing single-hand pose estimation algorithms are either subject to strong assumptions or depend on a weak detector to detect the human hand. We utilize Mask R-CNN to avoid both aforementioned constraints. The proposed framework allows detection of multi-hand instances and localization of hand joints simultaneously. Our experiments show that our method is superior to existing methods.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
004 Informatik

Schlagwörter

Konferenz

European Conference on Computer Vision (ECCV) 2018, 8. Sept. 2018 - 14. Sept. 2018, München
Rezension
undefined / . - undefined, undefined

Forschungsvorhaben

Organisationseinheiten

Zeitschriftenheft

Verknüpfte Datensätze

Zitieren

ISO 690DUAN, Le, Minmin SHEN, Song CUI, Zhexiao GUO, Oliver DEUSSEN, 2019. Estimating 2D Multi-hand Poses from Single Depth Images. European Conference on Computer Vision (ECCV) 2018. München, 8. Sept. 2018 - 14. Sept. 2018. In: LEAL-TAIXÉ, Laura, ed., Stefan ROTH, ed.. Computer Vision - ECCV 2018 Workshops : Munich, Germany, September 8-14, 2018, Proceedings, Part VI. Cham: Springer, 2019, pp. 257-272. Lecture Notes in Computer Science. 11134. ISSN 0302-9743. eISSN 1611-3349. ISBN 978-3-030-11023-9. Available under: doi: 10.1007/978-3-030-11024-6_17
BibTex
@inproceedings{Duan2019Estim-52400,
  year={2019},
  doi={10.1007/978-3-030-11024-6_17},
  title={Estimating 2D Multi-hand Poses from Single Depth Images},
  number={11134},
  isbn={978-3-030-11023-9},
  issn={0302-9743},
  publisher={Springer},
  address={Cham},
  series={Lecture Notes in Computer Science},
  booktitle={Computer Vision - ECCV 2018 Workshops : Munich, Germany, September 8-14, 2018, Proceedings, Part VI},
  pages={257--272},
  editor={Leal-Taixé, Laura and Roth, Stefan},
  author={Duan, Le and Shen, Minmin and Cui, Song and Guo, Zhexiao and Deussen, Oliver}
}
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/123456789/52400">
    <dc:rights>terms-of-use</dc:rights>
    <dc:creator>Cui, Song</dc:creator>
    <dc:creator>Shen, Minmin</dc:creator>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/52400/1/Duan_2-eag9rf9qwzit2.pdf"/>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2021-01-14T09:07:38Z</dcterms:available>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/52400/1/Duan_2-eag9rf9qwzit2.pdf"/>
    <dc:contributor>Deussen, Oliver</dc:contributor>
    <dc:creator>Duan, Le</dc:creator>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2021-01-14T09:07:38Z</dc:date>
    <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
    <dcterms:title>Estimating 2D Multi-hand Poses from Single Depth Images</dcterms:title>
    <dc:creator>Guo, Zhexiao</dc:creator>
    <dcterms:abstract xml:lang="eng">We present a novel framework based on Pictorial Structure (PS) models to estimate 2D multi-hand poses from depth images. Most existing single-hand pose estimation algorithms are either subject to strong assumptions or depend on a weak detector to detect the human hand. We utilize Mask R-CNN to avoid both aforementioned constraints. The proposed framework allows detection of multi-hand instances and localization of hand joints simultaneously. Our experiments show that our method is superior to existing methods.</dcterms:abstract>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:language>eng</dc:language>
    <dc:contributor>Shen, Minmin</dc:contributor>
    <dc:contributor>Cui, Song</dc:contributor>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dc:contributor>Guo, Zhexiao</dc:contributor>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:creator>Deussen, Oliver</dc:creator>
    <dcterms:issued>2019</dcterms:issued>
    <dc:contributor>Duan, Le</dc:contributor>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/52400"/>
  </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