Investigating Depth-Based Target Expansion for Gaze Selection with Dwell Activation in Virtual Environments

While dwell-based selection enables interaction with little physical effort, it is prone to (eye) gaze jitter. Target expansion methods mitigate this problem by increasing the effective selectable target area in 2D environments. Yet depth-related factors may limit their effectiveness in 3D virtual environments due to stereo-deficiencies. In this paper, we investigate how depth affects target expansion methods for dwell-based gaze selection, and propose DEPTH-BASED expansion, a method that adapts target expansion based on depth. We conducted two user studies to evaluate our proposed method with an ISO 9241:411 multidirectional selection study and a 3D selection study in a complex environment. Our results show that while the effectiveness of 2D target expansion methods decreases significantly with increasing depth, our proposed method consistently improved user performance and experience. Our findings provide design insights for effective dwell-based selection of expanding targets in 3D virtual environments.