3D Ternary-Gaussian model: Modeling pointing uncertainty of 3D moving target selection in virtual reality

Abstract

This paper presents a 3D Ternary-Gaussian model that describes the uncertainty of pointing at 3D moving targets in virtual reality. In contrast to 2D user interfaces, users’ perception and acquisition abilities for 3D moving targets may undergo dynamic changes due to the influence of target depth, rendering the modeling of 3D moving target selection more challenging and intricate. We address this issue by categorizing the effects of depth on moving target selection as arm movement stability and visual perception, and then integrating these effects into a previously proposed Ternary-Gaussian model framework. A user study involving 15 participants was conducted to validate the model’s performance across three types of target motions (i.e., motion-on-sphere, motion-in-depth, and combined motion). We conclude the paper with a set of implications for future design related to the selection of moving targets in 3D space.