CS assistant professor Yuhang Zhao developing AI and AR technology to support day-to-day activities of people with low vision
and current low vision aids like magnification, which distort users’ natural vision or diminish important details for these activities, can’t effectively support them. “As opposed to generic enhancements that apply to a low vision user’s full field of view, our research will leverage state-of-the-art AI technology to semantically understand the users’ environments and provide tailored, unobtrusive feedback only at necessary locations and time,” says Zhao.
The grant also allows Zhao to establish an annual workshop with the co-PIs Yapeng Tian from the University of Texas at Dallas and Jon E. Froehlich from the University of Washington, the local blind and low-vision communities (e.g., the Wisconsin Council of the Blind & Visually Impaired, the Wisconsin Office for the Blind and Visually Impaired), and rehabilitation organizations (e.g., UW-Madison Vision Rehabilitation Services) to present the work the team is doing and discuss opportunities and collaboration plans. This workshop will not only help the team collaborate but will also increase exposure of the low-vision community to state-of-the-art technology.
Another step toward Zhao’s research goals is a Best Paper Award (Belonging & Inclusion Track) at the ACM Symposium on User Interface Software and Technology (UIST) 2024, a top tier conference on technical human-computer interaction. The paper, entitled “CookAR: Affordance Augmentations in Wearable AR to Support Kitchen Tool Interactions for People with Low Vision,” introduces a tool for people with low vision to help them with the challenges of cooking.

CookAR: a wearable AR system that distinguishes and augments the different interaction areas of kitchen tools (e.g., knife blade vs. knife handle) to facilitate safe and efficient tool interaction for low vision users.