  The number of visually impaired or blind (VIB) people in the world is
estimated at several hundred million. Based on a series of interviews with the
VIB and developers of assistive technology, this paper provides a survey of
machine-learning based mobile applications and identifies the most relevant
applications. We discuss the functionality of these apps, how they align with
the needs and requirements of the VIB users, and how they can be improved with
techniques such as federated learning and model compression. As a result of
this study we identify promising future directions of research in mobile
perception, micro-navigation, and content-summarization.
