A1 Journal article (refereed)
Research on the factors affecting accuracy of abstract painting orientation detection (2023)
Zhao, Q., Chang, Z., & Wang, Z. (2023). Research on the factors affecting accuracy of abstract painting orientation detection. Multimedia Tools and Applications, 82, 36231-36254. https://doi.org/10.1007/s11042-023-15034-4
JYU authors or editors
Publication details
All authors or editors: Zhao, Qiang; Chang, Zheng; Wang, Ziwen
Journal or series: Multimedia Tools and Applications
ISSN: 1380-7501
eISSN: 1573-7721
Publication year: 2023
Publication date: 17/03/2023
Volume: 82
Pages range: 36231-36254
Publisher: Springer
Publication country: United States
Publication language: English
DOI: https://doi.org/10.1007/s11042-023-15034-4
Publication open access: Not open
Publication channel open access:
Abstract
An abstract painting’s hanging orientation directly affects how audiences judge its artistic value. Choosing the optimal hanging orientation can preserve the artist’s primary intention, preserving the original aesthetic value to a greater extent. Aesthetic value is frequently influenced by human subjective consciousness. Previous approaches improved direction recognition accuracy only by improving the feature extraction method and deep learning network. For this paper, the key factors that can influence recognition accuracy (such as painting content, image features and learning models) were investigated in conjunction with painting skills to find an experimental setting method that can enhance recognition accuracy. Experiment results show that the content of the painting has the greatest impact on classification accuracy. Furthermore, the average accuracy can be increased to more than 90% by reducing the number of painting categories in a dataset and the number of directions to be classified. While the outcome is superior to the state of the art, it is one-sided to rely solely on the information in the abstract painting. A combination of eye tracker data and questionnaires will be used in the future to examine the effect of audience subjective feelings on orientation classification.
Keywords: abstract art; recognition; neural networks (information technology)
Free keywords: orientation detection; abstract paintings; recognition accuracy; image feature; deep neural network
Contributing organizations
Ministry reporting: Yes
Reporting Year: 2023
Preliminary JUFO rating: 1
