The purpose of this research is to develop a fashion design perception computational model, taking shirts as an example. Fashion design perception computational modeling has emerged as a new scientific field that studies representing, modeling and understanding of fashion design perception. Unlike traditional behavior, fashion design perceptual activity is rather qualitative and explicit. The designer's cognitive activity in the design process represents the designer's accumulated thinking (style image) about garment components in the long-term design practice. Its modeling can be beneficial to fashion intelligent design. But its development is difficult since fashion design perception represents the designer's knowledge, which is rather complex.
This model is developed based on a sensory evaluation and fuzzy logic integrated method.
Findings reveal that a shirt component matrix and a perceptual description space are developed. Then, sensory evaluation experiments are carried out by experienced designers to extract the mapping relationship between the shirt component matrix and perceptual description space. After that, as the experiments are semantic data, fuzzy logic is employed to quantify the experiment data and perform mathematical computation. Finally, a fashion design perception computing model is established and verified.
The proposed fashion design perception computing model can be further applied to fashion individualized design. The method used to establish the model can be applied to developing perception computing models for other products.
