Automatic Analysis of Human Body Representations in Western Art

Publication date

2023-02-15

Authors

Zhao, Shu
Akdağ Salah, A. A.ORCID 0000-0002-7204-5633ISNI 0000000050543653
Salah, A.A.ORCID 0000-0001-6342-428XISNI 0000000091147032

Editors

Karlinsky, Leonid
Michaeli, Tomer
Nishino, Ko

Advisors

Supervisors

Document Type

Part of book
Open Access logo

License

taverne

Abstract

The way the human body is depicted in classical and modern paintings is relevant for art historical analyses. Each artist has certain themes and concerns, resulting in different poses being used more heavily than others. In this paper, we propose a computer vision pipeline to analyse human pose and representations in paintings, which can be used for specific artists or periods. Specifically, we combine two pose estimation approaches (OpenPose and DensePose, respectively) and introduce methods to deal with occlusion and perspective issues. For normalisation, we map the detected poses and contours to Leonardo da Vinci's Vitruvian Man, the classical depiction of body proportions. We propose a visualisation approach for illustrating the articulation of joints in a set of paintings. Combined with a hierarchical clustering of poses, our approach reveals common and uncommon poses used by artists. Our approach improves over purely skeleton based analyses of human body in paintings.

Keywords

Hierarchical clustering, Human pose estimation, Painting analysis, Taverne, Theoretical Computer Science, General Computer Science

Citation

Zhao, S, Akdağ Salah, A A & Salah, A 2023, Automatic Analysis of Human Body Representations in Western Art. in L Karlinsky, T Michaeli & K Nishino (eds), Computer Vision – ECCV 2022 Workshops : Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part I. 1 edn, Lecture Notes in Computer Science , vol. 13801 , Springer, Cham, pp. 282–297. https://doi.org/10.1007/978-3-031-25056-9_19