AI-Powered Interactive Systems that Improve Video Accessibility for Blind and Low Vision Viewers

PhD Qualifying Examination


Title: "AI-Powered Interactive Systems that Improve Video Accessibility for 
Blind and Low Vision Viewers"

by

Mr. Shuchang XU


Abstract:

Video has become a central medium for communication, education, and 
entertainment, yet it remains largely inaccessible to blind and low vision 
(BLV) viewers, who often lack access to the visual information essential for 
understanding videos. The primary approach for making videos accessible is 
audio description (AD), which provides spoken narration of key visual 
elements alongside the video. However, current AD practices face two 
primary challenges: the labor-intensive process of creating AD and the lack 
of interactivity to accommodate diverse viewer needs. This survey presents a 
comprehensive review of AI-powered interactive systems developed to address 
these challenges. We classify prior work into two main categories: (1) 
audio description creation, which leverages AI to enhance the efficiency 
and scalability of AD creation; and (2) viewer interaction, which enables 
BLV viewers to explore video content according to their individual 
information needs. Using this taxonomy, we analyze representative systems, 
identify emerging research trends, and discuss future directions toward more 
coherent, context-aware, and immersive video experiences for BLV audiences.


Date:                   Wednesday, 26 November 2025

Time:                   9:00am - 11:00am

Venue:                  Room 4472
                        Lifts 25/26

Committee Members:      Prof. Huamin Qu (Supervisor)
                        Dr. Xiaojuan Ma (Chairperson)
                        Dr. Anyi Rao (AMC)