An intelligent epistemological tool for audiovisual analysis and mediation of video art archive
| Authors | |
|---|---|
| Year of publication | 2024 |
| Type | Article in Periodical |
| Magazine / Source | Journal of Cultural Herritage |
| MU Faculty or unit | |
| Citation | |
| web | https://www.sciencedirect.com/science/article/abs/pii/S1296207424001353?via%3Dihub |
| Doi | http://dx.doi.org/10.1016/j.culher.2024.06.011 |
| Keywords | Analysis; Artificial intelligence; Augmented iconography; Deep learning; Intelligent epistemological tool; Video art |
| Description | 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. |
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