Teachable object recognizers for the blind

Abstract

Advances in artificial intelligence and computer vision hold great promises for increasing access to information and improving the quality of life for people with visual impairments. However, these recent technologies require an abundance of training data, which are typically obtained from sighted users. These training images tend to have different characteristics from images taken by blind users due to inherent differences in camera manipulation. My research focus is to build a teachable object recognizer, where blind users can actively train the underlying model with objects in proximity to their hand(s). Thus, the datasets used in my project are more representative of the blind population. In this article, I describe my research motivations and goals, and summarize my research plan.