Simultaneous Kansei Analysis of Evaluators, Objects and Words by Tensor SOM

Abstract

The aim of this research is to develop a method for kansei analysis. The proposed method using Tensor SOM generates three maps, which are the low dimensional visualizations of the evaluators, the evaluation objects, and the evaluation words. Furthermore it is also possible to visualize the relationships between them by coloring the maps. We applied the method to a kansei analysis of landscape images, and it showed us what kind of impression each image has and how the impression varies depending on the evaluators. Finally, we applied this method to a practical task in which we analyzed the instrument panel designs of automobiles.