The last few years have seen an explosion of medieval images in digital form, chiefly as a result of photo-library and manuscript digitisation projects. An entire corpus of images, even selected solely by scene or iconography, becomes an unwieldy object of study by traditional art-historical means. This is even more the case for medieval images, where authorship and dating are often cloudy and unclear, and the image itself is in many cases the first resource for scholarly inquiry.We take the digital image – in particular, the digital image of the body – as our object of study in a wide-ranging computationally-augmented reading of an image-corpus; ours is made up of thousands of depictions of the ‘Annunciation’ and ‘Baptism’, selected not only for their primacy in Christian art but for their dialogical interaction. Our corpus of 6,564 ‘Annunciations’ and 883 ‘Baptisms’, whilst not necessarily representative in density, includes a wide range of stylistic, theological and historical tendencies.We computationally extract not only body images but poses, gestures and interactions. Such a range of gestures allows for a morphological treatment of bodily motifs, whose multi-dimensional, quantitative nature allows us to complicate and problematise iconographic taxonomies, populating the spaces between categories. Finally, our gestural manifolds provide a morphological pointer to dissecting the microtemporalities of the scenes, and their relative dynamics and inconsistencies.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.