Research on the Architecture of Digital Song and Dance Costume Design System Based on Intelligent Deep Learning Algorithm

• Published in: Journal of sensors Vol. 2022; pp. 1 - 10
• Main Author: Wang, Wenli
• Format: Journal Article
• Language: English
• Published: New York Hindawi 07.02.2022; John Wiley & Sons, Inc
• Subjects: Algorithms; Clothing industry; Convex analysis; Costumes; Dance; Deep learning; Design; Feasibility studies; Intelligence; Machine learning; Optimization; Performance tests; R&D; Research & development; Software; Sparse matrices; Textiles; Virtual reality; Workflow; Yarn; United States > US; Japan
• ISSN: 1687-725X; 1687-7268; 1687-7268
• DOI: 10.1155/2022/1545334

In order to improve the intelligence and reliability of song and dance costume design, this article combines the intelligent deep learning algorithm to improve the digital costume design process. In order to solve the problem of minimizing the energy of image deformation, this paper proposes to transform it into a sparse matrix to solve the problem, which is solved by constructing a coefficient matrix and multiple iterations. After the algorithm is improved, this article combines the digital intelligence method to construct the digital song and dance costume design system structure based on the intelligent deep learning algorithm and analyzes its work flow. Finally, this paper verifies the method in this paper through feasibility analysis and system performance test. From the experimental results, it can be seen that the digital song and dance costume design system based on the intelligent deep learning algorithm proposed in this article has a good effect in the song and dance costume design.