Analysis of AIGC-Based Virtual Apparel Design System as An Alternative to Traditional Manual Design Process

Abstract

Traditional manual design is often overly complex and time-consuming to measure, leading to its gradual elimination from the market. To achieve digital design in clothing, this paper aims to realize the personalization and virtuality of modern clothing design while reducing design costs. This paper designs a virtual clothing design system based on AIGC, combining web interface design processes to simulate customized design content, and introduces a particle-spring model for mechanical analysis. It explores collision detection and response methods between the human body and clothing using AABB bounding boxes. Through experiments with 30 samples, the reliability and accuracy of the proposed method are validated, and cotton and silk garments are selected for design rationality prediction. The experiment on the design rationality prediction of silk clothing showed that the correlation coefficient between the predicted values of the BP prediction model and the measured values was 75.22%, while the correlation coefficient of the method proposed in this paper was 90.33%. Thus, the method proposed in this paper has a better prediction effect on the design rationality of silk clothing. The AIGC-based virtual clothing design system has a better alternative to the traditional manual design process.