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Nonverbal Communication in Medieval Illustrations Revisited by Computer Vision and Art History

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This contribution discusses how computer vision combined with art history can analyze the visual codes and artistic representations of embodied communication represented in medieval culture. Our computer-based detection algorithms are able to search directly for gestures in images and thus avoid limitations of retrieval systems that search only textual annotations. As a result, art history is provided not only with a system that enables efficient access to large image datasets, but also a quantitative analysis of the variability and interrelation among gestures or between gestures and other objects.

We base our approach on one of four illustrated manuscripts of Eike von Repgow's (ca. 1180–ca. 1235) Sachsenspiegel (Mirror of the Saxons), which reveals a visual grammar that arranges the gestures to a certain extent, but within that framework, the drafter composes freely and with artistic perspective.
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Keywords: Book Illumination; Computer Vision; Gestures; Heidelberg; Machine Learning; Middle Ages; Pattern Recognition; Sachsenspiegel; Visual Object Recognition; von Repgow; Eike (ca. 1180–ca. 1235)

Document Type: Research Article

Publication date: 2013-06-01

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