VisiMark: Characterizing and Augmenting Landmarks for People with Low Vision in Augmented Reality to Support Indoor Navigation

TL;DR

This work addresses how people with low vision (PLV) perceive landmarks and navigate indoors, proposing AR-based landmark augmentation to support orientation and mental map development. Through a formative study, the authors identify PLV-specific landmark categories and design VisiMark, featuring Signboards for overview and In-situ Labels for landmark-level augmentation, evaluated with 16 PLV. Results show VisiMark helps users perceive preferred, cognitively meaningful landmarks and shifts landmark selection from visually salient to meaningful landmarks, with improvements in perceived effectiveness and comfort. The study contributes a PLV-specific landmark taxonomy, design guidelines for AR augmentations, and practical insights for building AR navigation aids that prioritize safety, accessibility, and user agency in real-world environments.

Abstract

Landmarks are critical in navigation, supporting self-orientation and mental model development. Similar to sighted people, people with low vision (PLV) frequently look for landmarks via visual cues but face difficulties identifying some important landmarks due to vision loss. We first conducted a formative study with six PLV to characterize their challenges and strategies in landmark selection, identifying their unique landmark categories (e.g., area silhouettes, accessibility-related objects) and preferred landmark augmentations. We then designed VisiMark, an AR interface that supports landmark perception for PLV by providing both overviews of space structures and in-situ landmark augmentations. We evaluated VisiMark with 16 PLV and found that VisiMark enabled PLV to perceive landmarks they preferred but could not easily perceive before, and changed PLV's landmark selection from only visually-salient objects to cognitive landmarks that are more important and meaningful. We further derive design considerations for AR-based landmark augmentation systems for PLV.

Figures (5)

• Figure 1: (A) A bright hallway with a reflective floor, where shadows on the floor look like a ladder; (B-C) Staircases under different lighting conditions: dark vs. bright; (D) A ramp with railings as a landmark; (E) Danger signs as landmarks.
• Figure 2: Perceived "silhouette" of an area: (A-B) Two similar hallways. (C-D) Blurred to simulate how the "silhouette" of an area looks to PLV, where similar hallways have different color blocks.
• Figure 3: VisiMark design features: (A) Signboards that provide an overview of hallway structures and upcoming landmarks; (B) Color-coded hallways and their virtual representations (i.e., arrows) on the Signboard; (C) In-situ Labels with icons and texts for individual landmarks. (D) The dead-end marker at the tip of an arrow to represent the left hallway is a dead end.
• Figure 4: Four routes in the study environment with labeled landmarks augmented in VisiMark, including both those along the routes and other landmarks in the space displayed on Signboards. Detailed landmarks and their types for each route are listed on the right.
• Figure 5: Examples of participants' mental maps: (A) T7's mental map of route 1 with VisiMark, and (B) T7's mental map of route 2 without VisiMark. We observed a landmark selection shift here, as T7 chose more meaningful cognitive landmarks with VisiMark.