Research on Artificial Intelligence Painting APP Interface Design Based on Kansei Engineering

Abstract

Amidst the global dissemination of information and the rapid advancement of AI technology, AI painting has received extensive attention within the industry. Increasingly, designers are leveraging AI painting to enhance both the quality and efficiency of their designs. However, prevalent AI painting designs often neglect users’ genuine needs and psychological considerations. In response to this issue, the entropy weight-TOPSIS method and Kansei engineering theory have been employed to construct a technical architecture for the interface design of AI painting APPs. Through a comprehensive assessment encompassing user perceptual cognition and interface functionality, the effectiveness and practicability of the proposed method are validated using a case study involving an AI painting APP. The findings indicate that the method effectively evaluates the interface design, optimizes the design scheme, enhances user experience, and serves as a valuable reference for the future interface designs of AI painting APPs.