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The Semiotic and Computational Analysis of Represented Poses in Painting and Photography
Dondero, Maria Giulia; Deliège, Adrien
2026 • In Lecture Notes in Morphogenesis
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Keywords :
Computer vision; Gesture; Plastic semiotics; Pose estimation; Visual semiotics; Developmental Biology; Cognitive Neuroscience; Applied Mathematics
Abstract :
[en] This chapter focuses on the evolution of styles in the history of painting and retraces new genealogies of forms through recent deep learning-based computational methods applied to large image databases. This text associates the semiotic approach with the computational one offering a panorama of the most important current projects in Digital Art History. It proposes a particular conception of forms and forces in images, with the objective of making continuous bodily gestures analysable in large collections of paintings and photographs, starting from the works of art historians Henri Focillon and Aby Warburg. This conception of forces in images finds its roots in the Paris School Semiotics, but also in the work of philosopher Gilles Deleuze on pictorial diagrams in Francis Bacon’s painting and in mathematician René Thom’s idea of conflicting forces in painting.
Research Center/Unit :
Traverses - ULiège
Montefiore Institute - Montefiore Institute of Electrical Engineering and Computer Science - ULiège
Disciplines :
Computer science
Author, co-author :
Dondero, Maria Giulia  ;  Université de Liège - ULiège > Traverses
Deliège, Adrien  ;  Université de Liège - ULiège > Département d'électricité, électronique et informatique (Institut Montefiore) > Télécommunications
Language :
English
Title :
The Semiotic and Computational Analysis of Represented Poses in Painting and Photography
Publication date :
May 2026
Main work title :
Lecture Notes in Morphogenesis
Publisher :
Springer Verlag
ISBN/EAN :
978-3-03-208726-3
978-3-03-208725-6
Pages :
215-235
Peer reviewed :
Editorial reviewed
Name of the research project :
PDR FNRS Towards a Genealogy of Visual Forms: Semiotic and Computer-Assisted Approaches to Large Image Collections (2022-2025)
Funders :
F.R.S.-FNRS - Fonds de la Recherche Scientifique
Funding text :
T.0065.22
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since 11 August 2026

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