Kansei Analysis of the Japanese Residential Garden and Development of a Low-Cost Virtual Reality Kansei Engineering System for Gardens

Abstract

Residential garden design using Kansei engineering is a challenging problem. Landscaping components, such as rocks, trees, and ponds, are widely diversified and have a large number of possible arrangements. This large number of design alternatives makes conventional analyses, such as linear regression and its variations like Quantification Theory Type I (QT1), inapplicable for analyzing the relationships between design elements and the Kansei evaluation. We applied a partial least squares (PLS) model that effectively deals with a large number of predictor variables. The multiple correlation coefficient of the PLS analysis was much higher than that of the QT1 analysis. The results of the analyses were used to create a low-cost virtual reality Kansei engineering system that permits visualization of garden designs corresponding to selected Kansei words. To render complex garden scenes, we developed an original 3D computation and rendering library built on Java. The garden is shown in public-view style with stereo 3D graphic projection. The rendering is scalable from low to high resolution and enables drop object shadowing, which is indispensable for considering the effect of daytime changes in insolation. Visualizing the garden design based on Kansei analysis could facilitate collaboration between the designer and customer in the design process.