  People with color vision deficiency often face challenges in distinguishing
colors such as red and green, which can complicate daily tasks and require the
use of assistive tools or environmental adjustments. Current support tools
mainly focus on presentation-based aids, like the color vision modes found in
iPhone accessibility settings. However, offering context-aware support, like
indicating the doneness of meat, remains a challenge since task-specific
solutions are not cost-effective for all possible scenarios. To address this,
our paper proposes an application that provides contextual and autonomous
assistance. This application is mainly composed of: (i) an augmented reality
interface that efficiently captures context; and (ii) a multi-modal large
language model-based reasoner that serves to cognitize the context and then
reason about the appropriate support contents. Preliminary user experiments
with two color vision deficient users across five different scenarios have
demonstrated the effectiveness and universality of our application.
