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

<p>In this paper, Harris operator and DoG operator are used to extract visual features from images to ensure that a large number of useful feature points can be extracted in regions with little texture information. After determining the five main visual variables, virtual reality technology is used to conduct a preliminary exploration of the effect of visual variable perception in a three-dimensional model environment and to construct a mapping model of multiple visual variables. Combining the hardware and the visual variable mapping model, the design of the visual aesthetic element visualization system based on VR technology is completed, and the multiple visual variable mapping model is empirically analyzed using simulation analysis. The results show that the average accuracy of the qualitative test is as high as 65.73%, and the average time is as low as 7.02s, indicating that the visualization effect of the multiple visual variable model is obvious and alleviates the inadequacy of the ineffective color visualization scheme to a certain extent. This study analyzes the types and characteristics of visual aesthetic elements in the design industry and then proposes strategies for constructing visual aesthetic elements in graphic design to promote the sustainable development of the design industry.</p>
</abstract>

In this paper, Harris operator and DoG operator are used to extract visual features from images to ensure that a large number of useful feature points can be extracted in regions with little texture information. After determining the five main visual variables, virtual reality technology is used to conduct a preliminary exploration of the effect of visual variable perception in a three-dimensional model environment and to construct a mapping model of multiple visual variables. Combining the hardware and the visual variable mapping model, the design of the visual aesthetic element visualization system based on VR technology is completed, and the multiple visual variable mapping model is empirically analyzed using simulation analysis. The results show that the average accuracy of the qualitative test is as high as 65.73%, and the average time is as low as 7.02s, indicating that the visualization effect of the multiple visual variable model is obvious and alleviates the inadequacy of the ineffective color visualization scheme to a certain extent. This study analyzes the types and characteristics of visual aesthetic elements in the design industry and then proposes strategies for constructing visual aesthetic elements in graphic design to promote the sustainable development of the design industry.

Construction and visual expression of visual aesthetic elements based on VR technology

Applied Mathematics and Nonlinear Sciences

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

In this paper, Harris operator and DoG operator are used to extract visual features from images to ensure that a large number of useful feature points can be...

Construction and visual expression of visual aesthetic elements based on VR technology

Pubblicato online: 31 gen 2024

Pagine: -

Ricevuto: 20 dic 2023

Accettato: 30 dic 2023

DOI: https://doi.org/10.2478/amns-2024-0190

Parole chiave
Harris operator, DoG operator, Virtual reality technology, Visual variables, Mapping models

© 2024 Guobao Zhou et al., published by Sciendo

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

Construction and visual expression of visual aesthetic elements based on VR technology

Pubblicato online: 31 gen 2024

Pagine: -

Ricevuto: 20 dic 2023

Accettato: 30 dic 2023

DOI: https://doi.org/10.2478/amns-2024-0190

Parole chiaveHarris operator, DoG operator, Virtual reality technology, Visual variables, Mapping models

© 2024 Guobao Zhou et al., published by Sciendo

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

Parole chiave
Harris operator, DoG operator, Virtual reality technology, Visual variables, Mapping models