Overview
An interdisciplinary glossary on machine vision and aesthetics within the humanities and beyond.
The Aesthetics of Machine Vision brings together scholars, researchers, and artists who explore machine vision from various academic and nonacademic perspectives. Edited by Kathrin Maurer, Rikke Munck Petersen, Dominique Routhier, Kassandra Wellendorf, and Kristin Veel, this glossary creates a conversation between different terms (and scholars) and engages them in productive critical dialogue. The book constitutes a crucial forum where key terms in the discourse of machine vision can generate and enhance the understanding of these technologies and their societal ramifications. Hence, the book exceeds the idea of a glossary as a compendium of definitions within a specialized field. Rather, the entries in the book establish a heteroglossia across disciplines, thereby breaking new critical ground where different voices can learn from and enrich one another.
Machine vision entails a variety of advanced technologies that can extract information from and process images on an automated basis. They operate in society in the fields of inspection, observation, and production. The term “machine” refers not only to software—AI, deep learning, algorithms, imaging—but also to hardware as well as the wider material relations and operative contexts of machine vision. Its application spans traffic flow analysis, medical data analysis, agriculture, and security—fields as varied as the artists, architects, art historians, and critical theorists who have made machine vision their subject.
The Aesthetics of Machine Vision brings together scholars, researchers, and artists who explore machine vision from various academic and nonacademic perspectives. Edited by Kathrin Maurer, Rikke Munck Petersen, Dominique Routhier, Kassandra Wellendorf, and Kristin Veel, this glossary creates a conversation between different terms (and scholars) and engages them in productive critical dialogue. The book constitutes a crucial forum where key terms in the discourse of machine vision can generate and enhance the understanding of these technologies and their societal ramifications. Hence, the book exceeds the idea of a glossary as a compendium of definitions within a specialized field. Rather, the entries in the book establish a heteroglossia across disciplines, thereby breaking new critical ground where different voices can learn from and enrich one another.
Machine vision entails a variety of advanced technologies that can extract information from and process images on an automated basis. They operate in society in the fields of inspection, observation, and production. The term “machine” refers not only to software—AI, deep learning, algorithms, imaging—but also to hardware as well as the wider material relations and operative contexts of machine vision. Its application spans traffic flow analysis, medical data analysis, agriculture, and security—fields as varied as the artists, architects, art historians, and critical theorists who have made machine vision their subject.
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