Optimization of Human Perception on Virtual Garments by Modeling the Relation between Fabric Properties and Sensory Descriptors Using Intelligent Techniques

Abstract

3D virtual garment design using specific computer-aided-design software has attracted a great attention of textile/garment companies. However, there generally exists a perceptual gap between virtual and real products for both designers and consumers. This paper aims at quantitatively charactering human perception on virtual fabrics and its relation with the technical parameters of real fabrics. For this purpose, two sensory experiments are carried out on a small number of fabric samples. By learning from the identified input (technical parameters of the software) and output (sensory descriptors) data, we set up a series of models using different techniques. The fuzzy ID3 decision tree model has shown better performance than the other ones. © Springer International Publishing Switzerland 2014.