Development of Glasses Design Generation System using Impression Words Based on Deep Generative Model

Generally, in industrial design, sketching work is performed to search for the suitable shape and color for a concept including various impression word combinations. In sketching work, rookie designers take more time to reach shapes and colors that match the concept due to lack of knowledge and experience than skilled designers. Therefore, in this research, we developed a glasses design generation system that infers and visualizes suitable shapes of glasses from impression words using deep learning, aiming at educational effects for rookie designers. The purpose of the study is to clarify the relationship between impression words and shapes of glasses. In addition, to verify the usefulness of the system, we conducted an inference experiment on shapes of glasses for impression words with dimension compression by principal component analysis. As a result, it was confirmed that suitable shapes of the glasses for some impression words was inferred.