Publikation:

Automatic framework for tracking honeybee's antennae and mouthparts from low framerate video

Lade...
Vorschaubild

Dateien

Shen_261195.pdf
Shen_261195.pdfGröße: 119.13 KBDownloads: 368

Datum

2013

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

2013 IEEE International Conference on Image Processing. IEEE, 2013, pp. 4112-4116. ISBN 978-1-4799-2341-0. Available under: doi: 10.1109/ICIP.2013.6738847

Zusammenfassung

Automatic tracking of the movement of bee's antennae and mouthparts is necessary for studying associative learning of individuals. However, the problem of tracking them is challenging: First, the different classes of objects possess similar appearance and are close to each other. Second, tracking gaps are often present, due to the low frame-rate of the acquired video and the fast motion of the objects. Most existing insect tracking approaches have been developed for slow moving objects, and are not suitable for this application. In this paper, a novel Bayesian framework is proposed to automatically track bees' antennae and their mouthparts. This framework incorporates information about their kinematics, shape, order and temporal correlation between neighboring frames. Experimental evaluation demonstrates the effectiveness and efficiency of the proposed framework.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
570 Biowissenschaften, Biologie

Schlagwörter

Konferenz

2013 20th IEEE International Conference on Image Processing (ICIP), 15. Sept. 2013 - 18. Sept. 2013, Melbourne, Australia
Rezension
undefined / . - undefined, undefined

Forschungsvorhaben

Organisationseinheiten

Zeitschriftenheft

Zugehörige Datensätze in KOPS

Zitieren

ISO 690SHEN, Minmin, Paul SZYSZKA, C. Giovanni GALIZIA, Dorit MERHOF, 2013. Automatic framework for tracking honeybee's antennae and mouthparts from low framerate video. 2013 20th IEEE International Conference on Image Processing (ICIP). Melbourne, Australia, 15. Sept. 2013 - 18. Sept. 2013. In: 2013 IEEE International Conference on Image Processing. IEEE, 2013, pp. 4112-4116. ISBN 978-1-4799-2341-0. Available under: doi: 10.1109/ICIP.2013.6738847
BibTex
@inproceedings{Shen2013-09Autom-26119,
  year={2013},
  doi={10.1109/ICIP.2013.6738847},
  title={Automatic framework for tracking honeybee's antennae and mouthparts from low framerate video},
  isbn={978-1-4799-2341-0},
  publisher={IEEE},
  booktitle={2013 IEEE International Conference on Image Processing},
  pages={4112--4116},
  author={Shen, Minmin and Szyszka, Paul and Galizia, C. Giovanni and Merhof, Dorit}
}
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/123456789/26119">
    <dc:contributor>Galizia, C. Giovanni</dc:contributor>
    <dc:creator>Merhof, Dorit</dc:creator>
    <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
    <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/26119"/>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/26119/2/Shen_261195.pdf"/>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dc:rights>terms-of-use</dc:rights>
    <dc:language>eng</dc:language>
    <dc:creator>Szyszka, Paul</dc:creator>
    <dc:creator>Shen, Minmin</dc:creator>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/52"/>
    <dcterms:abstract xml:lang="eng">Automatic tracking of the movement of bee's antennae and mouthparts is necessary for studying associative learning of individuals. However, the problem of tracking them is challenging: First, the different classes of objects possess similar appearance and are close to each other. Second, tracking gaps are often present, due to the low frame-rate of the acquired video and the fast motion of the objects. Most existing insect tracking approaches have been developed for slow moving objects, and are not suitable for this application. In this paper, a novel Bayesian framework is proposed to automatically track bees' antennae and their mouthparts. This framework incorporates information about their kinematics, shape, order and temporal correlation between neighboring frames. Experimental evaluation demonstrates the effectiveness and efficiency of the proposed framework.</dcterms:abstract>
    <dc:contributor>Shen, Minmin</dc:contributor>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/52"/>
    <dcterms:title>Automatic framework for tracking honeybee's antennae and mouthparts from low framerate video</dcterms:title>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/28"/>
    <dc:creator>Galizia, C. Giovanni</dc:creator>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2014-02-17T14:33:45Z</dcterms:available>
    <dc:contributor>Merhof, Dorit</dc:contributor>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2014-02-17T14:33:45Z</dc:date>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/28"/>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:contributor>Szyszka, Paul</dc:contributor>
    <dcterms:issued>2013-09</dcterms:issued>
    <dcterms:bibliographicCitation>ICIP 2013 : IEEE International Conference on Image Processing, Sept. 15 - 18, 2013, Melbourne, Australia / International Conference on Image Processing &lt;2013, Melbourne&gt;. - Piscataway, NJ : IEEE, 2013. - S. 4112 - 4116. - ISBN 978-1-4673-2532-5</dcterms:bibliographicCitation>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/26119/2/Shen_261195.pdf"/>
  </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