Affiliations: [a] School of Architect & Fine Art, Dalian University of Technology, Dalian, Liaoning Province, China
| [b] School of Film & Television Art, Liaoning Normal University, Dalian, Liaoning Province, China
Correspondence:
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Corresponding author. Hongtu Ye, School of Architect & Fine Art, Dalian University of Technology, Dalian, Liaoning Province, 116000, China. E-mail: yehongtu2004@163.com.
Abstract: As the most popular art category in the contemporary art field, visual art is no longer limited to traditional art categories such as painting, sculpture and photography, but develops into more diverse forms of expression with the continuous iteration of science and technology. As the most cutting-edge and popular concept in the world today, the research, development and application of science and technology have attracted close attention from all walks of life, including management, economy, transportation, education and teaching. However, there is no in-depth and clear research between the concept of metaverse and the concept of metaverse in the art field, especially in the visual art field. We believe that visual art creation under the background of the metaverse will be an important direction of art development in the future, and will also greatly promote the improvement of the visual presentation quality of the metaverse. Therefore, we focus our research in this study on the issue of visual art quality assessment and propose a theory and method for assessing the quality of visual art in a future-oriented metaverse. This method is based on the G1 entropy method in fuzzy mathematics. In our research, we have built a visual art field architecture based on the metaverse. Considering the difference between the traditional visual art evaluation index system and the index system after the introduction of the concept of the future metaverse, we have built a brand-new visual art quality evaluation index system facing the future metaverse. This indicator is composed of four first-class indicators and twelve second-class indicators. We combine the subjective and objective weighting G1 entropy method as the method basis for the quantitative calculation results of the indicator weight. On the basis of quantitative analysis, we propose three-point countermeasures for improving the visual art quality of the future metaverse. Our research makes up for the gap in the theory of visual art quality evaluation after the introduction of the concept of the future metaverse, innovates the analysis of new concepts and the improvement of old methods, builds a new scene of organic combination of new technology and traditional visual art, and provides a new idea for the improvement of visual art quality in the future at home and abroad, It can also provide experience and theoretical support for the academic topic of similar art quality evaluation research at home and abroad.
Keywords: Visual arts, metaverse, field architecture, G1-entropy method, AHP method
