Ju Jiehui, Ma Yanghui, Gong Ting, Zhuang Er
School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou, 310023, Zhejiang, China.
Heliyon. 2024 Sep 5;10(17):e37478. doi: 10.1016/j.heliyon.2024.e37478. eCollection 2024 Sep 15.
This paper aims to explore the application of visual image big data (BD) in art management, and proposes and develops a new art management model. First of all, this study conducted extensive research on the overview and application of big data, focusing on analyzing the characteristics of big data and its characteristics and application methods in art management. By introducing image processing (IP) technology, this paper expounds on the application of visual image technology in art management in detail and discusses the classification of computer vision images to determine its application direction. On this basis, this paper proposes the application of visual images and big data in art management from three aspects: the accurate acquisition of visual images, the development model of art management, and the development of visual image technology in art resource management and teaching, and strengthens the development model of art management based on IP algorithm. Experiments and surveys show that the art management model development system built by the newly introduced visual image technology, big data technology, and IP algorithm can increase user satisfaction by 24 %. This result shows that the new model has a significant effect in improving the efficiency and quality of art management, providing strong technical support for the field of art management, while also providing designers with a more accurate tool for assessing market trends, helping to adhere to and promote good design concepts.
本文旨在探讨视觉图像大数据（BD）在艺术管理中的应用，并提出和开发一种新的艺术管理模式。首先，本研究对大数据的概述和应用进行了广泛研究，重点分析了大数据的特征及其在艺术管理中的特点和应用方法。通过引入图像处理（IP）技术，本文详细阐述了视觉图像技术在艺术管理中的应用，并讨论了计算机视觉图像的分类以确定其应用方向。在此基础上，本文从视觉图像的精准获取、艺术管理的发展模式以及视觉图像技术在艺术资源管理与教学中的发展三个方面提出了视觉图像与大数据在艺术管理中的应用，并强化了基于IP算法的艺术管理发展模式。实验和调查表明，新引入的视觉图像技术、大数据技术和IP算法构建的艺术管理模式开发系统可将用户满意度提高24%。这一结果表明，新模型在提高艺术管理效率和质量方面具有显著效果，为艺术管理领域提供了强大的技术支持，同时也为设计师提供了一个更准确的评估市场趋势的工具，有助于坚持和推广良好的设计理念。
