Abstract
The human face is a popular motif in art and depictions of faces can be found throughout history in nearly every culture. Artists have mastered the depiction of faces after employing careful experimentation using the relatively limited means of paints and oils. Many of the results of these experimentations are now available to the scientific domain due to the digitization of large art collections. In this paper we study the depiction of the face throughout history. We used an automated facial detection network to detect a set of 11,659 faces in 15,534 predominately western artworks, from 6 international, digitized art galleries. We analyzed the pose and color of these faces and related those to changes over time and gender differences. We find a number of previously known conventions, such as the convention of depicting the left cheek for females and vice versa for males, as well as unknown conventions, such as the convention of females to be depicted looking slightly down. Our set of faces will be released to the scientific community for further study.
Original language | English |
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Title of host publication | IS and T International Symposium on Electronic Imaging Science and Technology |
Editors | C. Damon, M. McCourt, J. Mulligan |
Number of pages | 8 |
Volume | 2020 |
Edition | 11 |
DOIs | |
Publication status | Published - 2020 |
Event | 2020 Human Vision and Electronic Imaging Conference, HVEI 2020 - Burlingame, United States Duration: 26 Jan 2020 → 30 Jan 2020 |
Publication series
Name | IS and T International Symposium on Electronic Imaging Science and Technology |
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Conference
Conference | 2020 Human Vision and Electronic Imaging Conference, HVEI 2020 |
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Country/Territory | United States |
City | Burlingame |
Period | 26/01/20 → 30/01/20 |
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Conventions and temporal differences in painted faces - A study of posture and color distribution
van Zuijlen, M. (Creator), Pont, S. C. (Creator) & Wijntjes, M. W. A. (Creator), TU Delft - 4TU.ResearchData, 13 Feb 2020
DOI: 10.4121/UUID:3BEEE8EF-1B7E-451F-966F-13230CB2BBE7
Dataset/Software: Dataset