基于AIGC技术的视觉传达与产品设计融合生成算法研究

IF 3.6
Guoying Chen, Xiaofeng Lan, Kai Liu, Can Cheng
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引用次数: 0

摘要

当前的视觉传达与产品设计领域面临着创意灵感获取效率低、设计流程繁琐、难以满足个性化需求等问题。本文分析了AIGC技术在视觉传达中的应用,包括AIGC生成模型在设计中的关键作用及其提高设计效率的方法。讨论了AIGC技术在产品设计中的应用及其对传统设计过程的改变,重点介绍了基于AIGC的自动设计生成方法。直脸与斜脸结合的设计提升了视觉层次,使得整体设计感知得分达到593分,比之前的设计提高了38分,说明视觉优化效果显著。在AIGC技术生成的设计方案中,颜色和材质的均匀性提高了4.66%,系统优化设计成功率为5.2%,进一步提高了设计的一致性和视觉感染力。本实验使用28个指标对感知表征模型进行了验证,为设计改进提供了稳健的数据基础。本文深入分析了视觉传达与产品设计融合的要求,提出了融合生成算法的基本框架和基于卷积神经网络的视觉传达与产品设计元素动态融合的方法。最后,通过实验分析验证了该算法的有效性和优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on fusion generation algorithm of visual communication and product design based on AIGC technology
The current field of visual communication and product design is faced with some problems, such as low efficiency of creative inspiration acquisition, cumbersome design process and difficult to meet personalized needs. This paper analyzes the application of AIGC technology in visual communication, including the key role of AIGC generation model in design and its methods to improve design efficiency. The application of AIGC technology in product design and its change to the traditional design process are discussed, and the automatic design generation method based on AIGC is emphatically introduced. The design of the combination of straight face and inclined face improves the visual hierarchy, making the overall design perception score reach 593 points, which is 38 points higher than the previous design, indicating that the visual optimization effect is remarkable. In the design scheme generated by AIGC technology, the uniformity of color and material is improved by 4.66 %, and the success rate of systematic optimization design is 5.2 %, further improving the consistency and visual appeal of the design. In this experiment, the perceptual characterization model is validated using 28 indicators, providing a robust data foundation for design improvement. This paper makes an in-depth analysis of the requirements of fusion of visual communication and product design, and puts forward the basic framework of fusion generation algorithm and the method of dynamic fusion of visual communication and product design elements based on convolutional neural network. Finally, the effectiveness and advantages of the proposed algorithm are verified by experimental analysis.
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