Correction of Depth Perception in Virtual Environment Using Spatial Compnents and Perceptual Clues

Abstract

As the education and training is such a virtual environment is applied to various fields, its usability is endless. However, there is an underestimation of the depth of perception in the training environment. In order to solve this problem, we tried to solve the problem by applying the top-down correction method. However, it is difficult to classify the result as a learning effect or perception change. In this study, it was confirmed that the proportion of spatial components of urine had a significant effect on the depth perception, and it was confirmed that the size perception were corrected together. In this study, we propose a correction method using spatial component and depth perception to improve the accuracy of depth perception.