<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper explores the integration of computer visual art with digital media, highlighting the innovative potential of computer technology in creating dynamic digital media art. Initially, we review relevant theories of computer-based visual art and examine their applications in digital media art. We then detail an immersive scene design using Web3D technology, where images are processed via a computer vision camera imaging model, transformed, and analyzed with the SIFT algorithm to extract feature points. These are integrated with the incremental SFM algorithm for three-dimensional image reconstruction in immersive environments. We validate these methods with real datasets and controlled experiments to assess user experience improvements in digital media applications. Results indicate that the SIFT algorithm’s image-matching accuracy ranges from 50% to 78%, and the incremental SFM algorithm shows an average rotation error of only 0.183°. User sentiment scores improved significantly, from 11.583 to 23.452, post-experience, demonstrating enhanced realism and a new direction for digital media art.</p>
</abstract>

This paper explores the integration of computer visual art with digital media, highlighting the innovative potential of computer technology in creating dynamic digital media art. Initially, we review relevant theories of computer-based visual art and examine their applications in digital media art. We then detail an immersive scene design using Web3D technology, where images are processed via a computer vision camera imaging model, transformed, and analyzed with the SIFT algorithm to extract feature points. These are integrated with the incremental SFM algorithm for three-dimensional image reconstruction in immersive environments. We validate these methods with real datasets and controlled experiments to assess user experience improvements in digital media applications. Results indicate that the SIFT algorithm’s image-matching accuracy ranges from 50% to 78%, and the incremental SFM algorithm shows an average rotation error of only 0.183°. User sentiment scores improved significantly, from 11.583 to 23.452, post-experience, demonstrating enhanced realism and a new direction for digital media art.

Research on the Innovative Development of Digital Media Enabled by Computer Visual Arts

Zhejiang Gongshang University Hangzhou College of Commerce

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper explores the integration of computer visual art with digital media, highlighting the innovative potential of computer technology in creating dynamic...

Research on the Innovative Development of Digital Media Enabled by Computer Visual Arts

Online veröffentlicht: 15. Mai 2024

Seitenbereich: -

Eingereicht: 01. Feb. 2024

Akzeptiert: 15. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-1112

Schlüsselwörter
Web3D technology, Camera imaging model, SIFT algorithm, Incremental SFM algorithm, Computer vision, Digital media

© 2024 Shuang Dong, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on the Innovative Development of Digital Media Enabled by Computer Visual Arts

Online veröffentlicht: 15. Mai 2024

Seitenbereich: -

Eingereicht: 01. Feb. 2024

Akzeptiert: 15. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-1112

SchlüsselwörterWeb3D technology, Camera imaging model, SIFT algorithm, Incremental SFM algorithm, Computer vision, Digital media

© 2024 Shuang Dong, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Web3D technology, Camera imaging model, SIFT algorithm, Incremental SFM algorithm, Computer vision, Digital media