Skip to main content
SpringerLink
Log in

Computer-aided digital media art creation based on artificial intelligence

  • S.I.: Applications and Techniques in Cyber Intelligence (ATCI2022)
  • Published:
Neural Computing and Applications Aims and scope Submit manuscript

Abstract

Driven by information technology, artificial intelligence (AI) has gradually become an important symbol of modern society. In digital media art creation, AI has unique advantages and can help artists create better works. The purpose of this research was to study digital media art creation based on AI’s computer-aided technology. This study analysed the possibility of combining digital media art with AI and the positive effects of combining it with digital media art creation are discussed. A support vector machine (SVM) algorithm based on AI is proposed, and computer-aided digital media art creation based on AI was analysed experimentally. The experimental results of this study showed that artistic works created based on AI computer-aided technology had a digital dynamic score of 80 to 90, a digital sound effect score of 82 to 92, a digital stunt score of 85 to 95, a digital texture score of 83 to 96, and a digital colour score of 86 to 93. These scores were higher than those of works of art created based on traditional technology, indicating that AI-based computer-aided technology can be well applied to the creation of digital media art.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

References

  1. Ma D, Kim HG (2020) Shape of light: interactive analysis of digital media art based on processing. TECHART: J Arts Imaging Sci 7(4):23–29

    Article  Google Scholar 

  2. Linda C, Edmonds E (2018) Practice-based research in the creative arts: foundations and futures from the front line. Leonardo 51(1):63–69

    Article  Google Scholar 

  3. Martin Z (2018) Digital art as ‘monetised graphics’: enforcing intellectual property on the blockchain. Philos Technol 31(1):15–41

    Article  Google Scholar 

  4. Franceschet M, Colavizza G, Smith TA, Finucane B, Ostachowski ML, Scalet S et al (2021) Crypto art: a decentralized view. Leonardo 54(4):402–405

    Article  Google Scholar 

  5. Caixia He, Sun B (2021) Application of artificial intelligence technology in computer aided art teaching. Comput-Aided Des Appl 18(S4):118–129

    Article  Google Scholar 

  6. Sema K (2020) Prospective visual arts teachers’ innovation skills and attitudes towards computer assisted instruction. Int J Technol Educ Sci 4(2):98–107

    Article  Google Scholar 

  7. Hua J, Yang J (2021) Using computer-aided design software in teaching environmental art design. Comput-Aided Des Appl 19(S1):173–183

    Article  Google Scholar 

  8. Xiaolin W (2021) Building a parallel corpus for english translation teaching based on computer-aided translation software. Comput-Aided Des Appl 18(S4):175–185

    Article  Google Scholar 

  9. Fanwen K (2020) Application of artificial intelligence in modern art teaching. Int J Emerg Technol Learn (iJET) 15(13):238–251

    Article  Google Scholar 

  10. Jeong SM (2020) The application of digital fabrication technologies to the art and design curriculum in a teacher preparation program: a case study. Int J Technol Des Educ 30(4):687–707

    Article  Google Scholar 

  11. Martin Z, Luger J (2019) Digital geographies of public art: new global politics. Prog Hum Geogr 43(5):890–909

    Article  Google Scholar 

  12. Choe NS, Natalie RC (2019) Behind the screens: informed consent and digital literacy in art therapy. Art Ther 36(1):15–21

    Article  Google Scholar 

  13. Hew WW (2018) THE ART OF DAKWAH: social media, visual persuasion and the Islamist propagation of Felix Siauw. Indones Malay World 46(134):61–79

    Article  Google Scholar 

  14. Gjorgji S, Worring M (2018) Omniart: a large-scale artistic benchmark. ACM Trans Multimedia Comput, Commun, Appl (TOMM) 14(40):1–21

    Google Scholar 

  15. Michael W, Moser T (2019) The art of coding and thematic exploration in qualitative research. Int Manag Rev 15(1):45–55

    Google Scholar 

  16. Husic BE, Pande VS (2018) Markov state models: from an art to a science. J Am Chem Soc 140(7):2386–2396

    Article  Google Scholar 

  17. Keith N (2019) From creator to data: the post-record music industry and the digital conglomerates. Media Cult Soc 41(3):367–384

    Article  Google Scholar 

  18. Dunas DV, Vartanov SA (2020) Emerging digital media culture in Russia: modeling the media consumption of Generation Z. J Multicultur Discourse 15(2):186–203

    Article  Google Scholar 

  19. Cuihua S, Kasra M, Pan W, Bassett GA, Malloch Y, James F, OBrie (2019) Fake images: the effects of source, intermediary, and digital media literacy on contextual assessment of image credibility online. New Media Soc 21(2):438–463

    Article  Google Scholar 

  20. Mat SNS, Noor NAZM, Rahman MHA (2019) An entrepreneurship framework in the new venture creation among art education students. Int J Entrepreneurship 2(5):25–37

    Google Scholar 

Download references

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author information

Authors and Affiliations

  1. Cheung Kong School of Art&Design, Shantou University, Shantou, 515063, Guangdong, China

    Bozuo Zhao & Danping Zhan

  2. Circulo Health, Columbus, OH, 43215, USA

    Canlin Zhang

  3. School of Humanities and Laws, Hebei University of Technology, Tianjin, 300401, China

    Meng Su

Authors
  1. Bozuo Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Danping Zhan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Canlin Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Meng Su
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Danping Zhan.

Ethics declarations

Conflict of interest

The author(s) declared no potential conflicts of interest with respect to the research, author-ship, and/or publication of this article.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhao, B., Zhan, D., Zhang, C. et al. Computer-aided digital media art creation based on artificial intelligence. Neural Comput & Applic 35, 24565–24574 (2023). https://doi.org/10.1007/s00521-023-08584-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00521-023-08584-z

Keywords

Search

Navigation