Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Article . 2022
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Article . 2022
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Conference object . 2022
License: CC BY
Data sources: ZENODO
DBLP
Conference object
Data sources: DBLP
versions View all 3 versions
addClaim

Der Einsatz von Computer Vision-Methoden für Filme - Eine Fallanalyse für die Kriminalfilm-Reihe Tatort

Authors: Thomas Schmidt; Sarah Kurek;

Der Einsatz von Computer Vision-Methoden für Filme - Eine Fallanalyse für die Kriminalfilm-Reihe Tatort

Abstract

Wir präsentieren eine explorative Studie im Bereich Computer Vision (CV) und Filmanalyse. Als Fallbeispiel wird die berühmte Kriminalfilm-Reihe "Tatort" gewählt. Im Fokus stehen dabei gruppenbasierte Vergleiche zwischen den Filmen von 4 ErmittlerInnen-Teams/Städten. Als CV-Methoden werden state-of-the-art-Modelle der Objekt-, Alters-, Geschlechts- Emotions- und Ortserkennung auf Frames eines Korpus bestehend aus 13 Filmen exploriert. Die Ergebnisse zeigen, dass die Serie in den Folgen des ausgewählten Korpus eher in Innenräumen spielt, Trauer und Neutralität die häufigsten Emotionsausdrücke sind und in der Mehrzahl männliche Figuren die Frames dominieren. Obschon signifikante Unterschiede zwischen den ErmittlerInnen-Teams/Städten bestehen, sind diese gemäß Post-Hoc-Tests eher gering. Wir berichten über unsere Erfahrungen mit den ausgewählten Methoden, die Probleme mit speziellen Charakteristiken von Filmen haben und schließen mit dem Ziel in größeren Annotationsstudien Trainingsmaterial zur Optimierung von CV-Methoden zu sammeln. Ein Beitrag zur 8. Tagung des Verbands "Digital Humanities im deutschsprachigen Raum" - DHd 2022 Kulturen des digitalen Gedächtnisses.

Keywords

Bilder, Computer Vision, Tatort, Video, Programmierung, Filmwissenschaft, Multimedia, Objekterkennung, DHd2022, Filmanalyse, Emotionserkennung, Bilderfassung, Inhaltsanalyse

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
    OpenAIRE UsageCounts
    Usage byUsageCounts
    visibility views 3
    download downloads 10
  • 3
    views
    10
    downloads
    Powered byOpenAIRE UsageCounts
Powered by OpenAIRE graph
Found an issue? Give us feedback
visibility
download
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
0
Average
Average
Average
3
10
Green