An intelligent epistemological tool for audiovisual analysis
and mediation of video art archive

J 2024

An intelligent epistemological tool for audiovisual analysis and mediation of video art archive

HORÁKOVÁ, Jana; Pavel SIKORA; Štěpán MIKLÁNEK; Dušan BAROK; Jiří SCHIMMEL et al.

Základní údaje

Originální název

An intelligent epistemological tool for audiovisual analysis and mediation of video art archive

Název česky

Inteligentní epistemologický nástroj pro audiovizuální analýzu a zprostředkování archivu uměleckých videí

Autoři

HORÁKOVÁ, Jana; Pavel SIKORA; Štěpán MIKLÁNEK; Dušan BAROK; Jiří SCHIMMEL a Kamil ŘÍHA

Vydání

Journal of Cultural Herritage, Elsevier, 2024, 1778-3674

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

60401 Arts, Art history

Stát vydavatele

Nizozemské království

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 3.300

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14210/24:00139835

Organizační jednotka

Filozofická fakulta

Klíčová slova česky

Analýza; umělá inteligence; augumentovaná ikonografie; hluboké učení; inteligentní epistemologický nástroj; video art

Klíčová slova anglicky

Analysis; Artificial intelligence; Augmented iconography; Deep learning; Intelligent epistemological tool; Video art

Štítky

rivok

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 3. 11. 2025 11:45, doc. Mgr. Jana Horáková, Ph.D.

Anotace

V originále

This article focuses on the development and application of intelligent software for image and sound recognition to perform iconographic and audiographic analyses of the work of video art pioneers Steina and Woody Vasulka (the Vasulkas). The AI epistemological tool Vasulka Live Archive is designed to pro- vide unique results that benefit from the synthesis of automatic statistical analysis across the dataset and application of predefined categories that are the results of aesthetic evaluation of the Vasulkas’ videos and inspired by terminology of video art aesthetics (Weibel, Krauss). The advantages of this AI tool reveal themselves particularly when the tool is used for transmedia analysis of the whole dataset (the Vasulkas’ work) as the accuracy and completeness of its results are out of reach of an individual human researcher. We argue that this kind of AI tools can contribute to more exact and data-based findings on media art aesthetics, it can contribute to establishing a new field augmented iconology (Spratt) as well as expand- ing the sphere of AI tools application towards digital collections of experimental and conceptual art of 20th and 21st centuries.

Návaznosti

TL02000270, projekt VaV

Název: Media Art Live Archive: Inteligentní rozhraní pro interaktivní zprostředkování kulturního dědictví (Akronym: MediaArtLiveArchive)

Investor: Technologická agentura ČR, Media Art Live Archive: Inteligentní rozhraní pro interaktivní zprostředkování kulturního dědictví

Citovat

HORÁKOVÁ, Jana; Pavel SIKORA; Štěpán MIKLÁNEK; Dušan BAROK; Jiří SCHIMMEL a Kamil ŘÍHA. An intelligent epistemological tool for audiovisual analysis and mediation of video art archive. Journal of Cultural Herritage. Elsevier, 2024, roč. 68, July–August 2024, s. 298-306. ISSN 1778-3674. Dostupné z: https://doi.org/10.1016/j.culher.2024.06.011.

@article{2425581,
   author = {Horáková, Jana and Sikora, Pavel and Miklánek, Štěpán and Barok, Dušan and Schimmel, Jiří and Říha, Kamil},
   article_number = {July–August 2024},
   doi = {https://doi.org/10.1016/j.culher.2024.06.011},
   keywords = {Analysis; Artificial intelligence; Augmented iconography; Deep learning; Intelligent epistemological tool; Video art},
   language = {eng},
   issn = {1778-3674},
   journal = {Journal of Cultural Herritage},
   title = {An intelligent epistemological tool for audiovisual analysis and mediation of video art archive},
   url = {https://www.sciencedirect.com/science/article/abs/pii/S1296207424001353?via%3Dihub},
   volume = {68},
   year = {2024}
}

TY  - JOUR
ID  - 2425581
AU  - Horáková, Jana - Sikora, Pavel - Miklánek, Štěpán - Barok, Dušan - Schimmel, Jiří - Říha, Kamil
PY  - 2024
TI  - An intelligent epistemological tool for audiovisual analysis and mediation of video art archive
JF  - Journal of Cultural Herritage
VL  - 68
IS  - July–August 2024
SP  - 298-306
EP  - 298-306
PB  - Elsevier
SN  - 17783674
KW  - Analysis
KW  - Artificial intelligence
KW  - Augmented iconography
KW  - Deep learning
KW  - Intelligent epistemological tool
KW  - Video art
UR  - https://www.sciencedirect.com/science/article/abs/pii/S1296207424001353?via%3Dihub
N2  - This article focuses on the development and application of intelligent software for image and sound recognition to perform iconographic and audiographic analyses of the work of video art pioneers Steina and Woody Vasulka (the Vasulkas). The AI epistemological tool Vasulka Live Archive is designed to pro- vide unique results that benefit from the synthesis of automatic statistical analysis across the dataset and application of predefined categories that are the results of aesthetic evaluation of the Vasulkas’ videos and inspired by terminology of video art aesthetics (Weibel, Krauss). The advantages of this AI tool reveal themselves particularly when the tool is used for transmedia analysis of the whole dataset (the Vasulkas’ work) as the accuracy and completeness of its results are out of reach of an individual human researcher. We argue that this kind of AI tools can contribute to more exact and data-based findings on media art aesthetics, it can contribute to establishing a new field augmented iconology (Spratt) as well as expand- ing the sphere of AI tools application towards digital collections of experimental and conceptual art of 20th and 21st centuries.
ER  -

HORÁKOVÁ, Jana; Pavel SIKORA; Štěpán MIKLÁNEK; Dušan BAROK; Jiří SCHIMMEL a Kamil ŘÍHA. An intelligent epistemological tool for audiovisual analysis and mediation of video art archive. \textit{Journal of Cultural Herritage}. Elsevier, 2024, roč.~68, July–August 2024, s.~298-306. ISSN~1778-3674. Dostupné z: https://doi.org/10.1016/j.culher.2024.06.011.

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