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Understanding Gardar Sahlberg with neural nets : On algorithmic reuse of the Swedish SF archive

Eriksson, Maria ; Skotare, Tomas and Snickars, Pelle LU (2022) In Journal of Scandinavian Cinema 12(3). p.225-247
Abstract
In this article, we re-trace the history of the Swedish SF archive and reflect on how this collection of historic newsreels has been reappropriated and remixed throughout more recent media history. In particular, we focus on the work of director and film historian Gardar Sahlberg, who made extensive use of the SF archive, first in a series of documentary films, then in a number of historical TV programmes. We are interested in how historic film footage travels and circulates through time, but foremost we explore how algorithms can help identify instances of audio-visual reuse in large datasets. Hence the article discusses algorithmic ways of examining archival film reuse, introducing a method for mapping video reuse with the help of... (More)
In this article, we re-trace the history of the Swedish SF archive and reflect on how this collection of historic newsreels has been reappropriated and remixed throughout more recent media history. In particular, we focus on the work of director and film historian Gardar Sahlberg, who made extensive use of the SF archive, first in a series of documentary films, then in a number of historical TV programmes. We are interested in how historic film footage travels and circulates through time, but foremost we explore how algorithms can help identify instances of audio-visual reuse in large datasets. Hence the article discusses algorithmic ways of examining archival film reuse, introducing a method for mapping video reuse with the help of artificial intelligence or more precisely machine learning that uses so-called convolutional neural nets. The article presents the Video Reuse Detector (VRD), a tool that uses machine learning to identify visual similarities within a given audio-visual database such as the SF archive. (Less)
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author
; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
film archives, archival reuse, Video Reuse Detector, AI, convolutional neural nets, computational film studies
in
Journal of Scandinavian Cinema
volume
12
issue
3
pages
23 pages
publisher
Intellect Ltd.
external identifiers
  • scopus:85153482909
ISSN
2042-7891
DOI
10.1386/jsca_00075_1
language
English
LU publication?
yes
id
d1ca7182-29d3-4bb9-bdbf-ef909fff1dd3
date added to LUP
2023-03-02 10:34:33
date last changed
2024-02-03 11:52:35
@article{d1ca7182-29d3-4bb9-bdbf-ef909fff1dd3,
  abstract     = {{In this article, we re-trace the history of the Swedish SF archive and reflect on how this collection of historic newsreels has been reappropriated and remixed throughout more recent media history. In particular, we focus on the work of director and film historian Gardar Sahlberg, who made extensive use of the SF archive, first in a series of documentary films, then in a number of historical TV programmes. We are interested in how historic film footage travels and circulates through time, but foremost we explore how algorithms can help identify instances of audio-visual reuse in large datasets. Hence the article discusses algorithmic ways of examining archival film reuse, introducing a method for mapping video reuse with the help of artificial intelligence or more precisely machine learning that uses so-called convolutional neural nets. The article presents the Video Reuse Detector (VRD), a tool that uses machine learning to identify visual similarities within a given audio-visual database such as the SF archive.}},
  author       = {{Eriksson, Maria and Skotare, Tomas and Snickars, Pelle}},
  issn         = {{2042-7891}},
  keywords     = {{film archives; archival reuse; Video Reuse Detector; AI; convolutional neural nets; computational film studies}},
  language     = {{eng}},
  number       = {{3}},
  pages        = {{225--247}},
  publisher    = {{Intellect Ltd.}},
  series       = {{Journal of Scandinavian Cinema}},
  title        = {{Understanding Gardar Sahlberg with neural nets : On algorithmic reuse of the Swedish SF archive}},
  url          = {{http://dx.doi.org/10.1386/jsca_00075_1}},
  doi          = {{10.1386/jsca_00075_1}},
  volume       = {{12}},
  year         = {{2022}},
}