A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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-tekijät tai -toimittajat

Julkaisun tiedot

Julkaisun kaikki tekijät tai toimittajat: Zhao, Qiang; Chang, Zheng; Wang, Ziwen

Lehti tai sarja: Multimedia Tools and Applications

ISSN: 1380-7501

eISSN: 1573-7721

Julkaisuvuosi: 2023

Ilmestymispäivä: 17.03.2023

Volyymi: 82

Artikkelin sivunumerot: 36231-36254

Kustantaja: Springer

Julkaisumaa: Yhdysvallat (USA)

Julkaisun kieli: englanti

DOI: https://doi.org/10.1007/s11042-023-15034-4

Julkaisun avoin saatavuus: Ei avoin

Julkaisukanavan avoin saatavuus: 

Tiivistelmä

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.

YSO-asiasanat: abstrakti taide; tunnistaminen; neuroverkot

Vapaat asiasanat: orientation detection; abstract paintings; recognition accuracy; image feature; deep neural network

Liittyvät organisaatiot

OKM-raportointi: Kyllä

Raportointivuosi: 2023

Alustava JUFO-taso: 1