3D Aided Art Design Method Based on Improved Particle Swarm Optimization Algorithm

Abstract

Computer-aided design (CAD) has been applied more and more in the field of art design, which has become an indispensable tool for art designers, and art design has also ushered in a new development opportunity. Artificial intelligence (AI) is widely used in art design, which can better interpret the designer's interpretation of works and their design concepts artistically and present them to people. In this article, the characteristics of color images of artworks are analyzed, and a deep learning (DL) model based on improved particle swarm optimization (PSO) algorithm is used to track and extract the contours of artworks, so as to realize the recognition of color characteristics, and the CAD 3D reconstruction of artworks is completed according to the recognition results. The comprehensive results show that this method not only improves the efficiency of artistic image processing compared with the traditional DL method, but also has obvious advantages in image recognition accuracy. Therefore, the improved PSO algorithm is used to optimize the CAD modeling stage of artworks, which can locate the edge contour of artworks relatively accurately on the premise of ensuring the clarity of artworks images, thus improving the efficiency of artistic design and expanding the artistic design ideas.