Paper ID:250655W2
Authos: Yasuyuki Saito and Eita Nakamura
Title: Temporal variations in frequency of color use relative to position in portrait paintings
Publisher: Algorithm_Lab.
Conference: ICAITD 2025: The Second International Conference of AI new Technology and open Discussion
Location: Pleasanter Lounge Nakano, Tokyo Japan
Date: 1-4 june 2025
Editor: Kazuo Ohzeki (Algorithm_Lab. Professor Emeritus of Shibaura Institute of Technology, Professor of Emeritus of International Professional University of Technology in Tokyo)
Citation: Proceedings: ICAITD 2025
https://doi.org/10.63211/j.p.25.645332
pages: 79-82
Abstract:
As the times change, various styles and techniques of paintings have been created, and in recent years, advances in generative AI have made it possible to create very natural and realistic artificial paintings. In this paper, we focus on paintings obtained from WikiArt that are labeled as portrait and self-portrait, divide the canvas of the painting into sections, and focus on the temporal variations in the frequency of color use in each section over the years. The results of the experiments showed that red was used above a certain quantity, green was hardly used at all, and blue had been used less frequently since the 17th century. No significant differences were observed in these characteristics across the years for each section. In the future, when generative AI is used to create portraits, it is conceivable that there will be two possibilities: one is to simulate human creative activities by reflecting these characteristics, and the other is to overturn it by using new methods of using color.
Keywords: Paintings, WikiArt, Portrait, Hue, Frequency of color use relative to position
Category: Workshop Papers (IW-AITD 2025 is a joint workshop with ICAITD 2025)
Review process: Committee review
Publication date: July 2nd 2025
First received date: Jan. 1st 2025
Copyright :Author(Full), AlgorithmLab.(First-in-the-world publishing rights granted by the author as the Prceedings of ICAITD 2025)
Licence:Viewer can download and view this review paper, but cannot secondary distribute (redistribute) it. (It is not Creative Commons License, nor MIT Licence) In other words, "Do not distribute" is the License
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