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Distant Viewing: Computational Exploration of Digital Images
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Description
A new theory and methodology for the application of computer vision methods to the computational analysis of collected, digitized visual materials, called “distant viewing.”
Distant Viewing: Computational Exploration of Digital Images presents a new theory and methodology for the computational analysis of digital images, offering a lively, constructive critique of computer vision that you can actually use. What does it mean to say that computer vision “understands” visual inputs? Annotations never capture a whole image. The way digital images convey information requires what researchers Taylor Arnold and Lauren Tilton call “distant viewing”—a play on the well-known term “distant reading” from computational literary analysis.
Recognizing computer vision's limitations, Arnold and Tilton's spirited examination makes the technical exciting by applying distant viewing to the sitcoms Bewitched and I Dream of Jeannie, movie posters and other popular forms of advertising, and Dorothea Lange's photography. In the tradition of visual culture studies and computer vision, Distant Viewing's interdisciplinary perspective encompasses film and media studies, visual semiotics, and the sciences to create a playful, accessible guide for an international audience working in digital humanities, data science, media studies, and visual culture studies.
ISBN
9780262375160
Publication Date
2023
Publisher
MIT Press
DOI
10.7551/mitpress/14046.003.0014
School
School of Arts and Sciences
Department
Computer Science
Disciplines
Computer Sciences | Graphics and Human Computer Interfaces | Rhetoric
Recommended Citation
Arnold, T., & Tilton, L. C. (2023). Distant viewing: Computational exploration of digital images. MIT Press. https://doi.org/10.7551/mitpress/14046.001.0001
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Comments
© 2023 Massachusetts Institute of Technology Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Public License The open access edition of this book was made possible by generous funding and support from the author This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License .