Head, Gaze, or Finger? Comparing Object Selection Techniques in Augmented Reality for People with Low Vision

Abstract

Augmented reality (AR) can enhance visual perception for people with low vision (PLV) by overlaying multimodal information. Selection-based augmentation further allows users to flexibly choose and augment relevant information while reducing distraction and visual clutter. However, little is known about the ability and preferences of PLV in performing object selection techniques in AR, considering their potential visual and gaze control challenges. To understand what selection techniques are suitable for PLV to support selection-based AR augmentations, we conducted a mixed-methods study with 20 PLV and 18 sighted controls who performed target selection tasks using three input techniques -- head, gaze, and finger pointing with dwell-based confirmation -- in two real-world scenarios (sitting vs. on the go). We found that for PLV, gaze-based selection enabled the fastest initial pointing when sitting and comparable overall selection time to head-based selection in both scenarios; however, due to reduced gaze stability, head-based selection remained the most stable and the least mentally demanding. Uniquely, participants with central vision loss preferred finger-based selection, reporting a greater sense of control. Our results provide empirical insights into accessible AR interaction techniques and selection-based vision enhancements for PLV.