Size-Encoding methods for depth information in augmented reality

Abstract

In augmented reality (AR), bias in depth perception is a typical problem faced by users. Size encoding can provide useful depth cues to help AR users establish a connection between the augmented layer and the real world. This study aims to develop size encoding rules for augmented labelling of indoor spatial objects designed to represent depth layers on the basis of experimental research on human depth and size perception. In this study, we conducted two psychophysical experiments using the HoloLens 2. The depth perception stratification experiment provided a fitted relationship between subjective depth perception and physical depth, along with just noticeable difference (JND) values for depth perception. The size encoding experiment calculates the JND values for size differences. On the basis of the experimental results, we developed a list of depth information layers and size encoding layers for indoor spaces and proposed an augmented labelling size encoding method that effectively represents depth information.

The method can be applied to augmented information labelling in indoor spaces, and it has value for application in extended reality with overlay displays, which can be extended to virtual reality, augmented reality, and mixed reality devices.