Sensory Substitution of Vision - A Systematic Mapping and a Deep Learning Object Detection Proposition


Since 1946 methods for sensory substitution of vision has been studied; however, half a century after the beginning of this line of research, this keep been a massive problem in a world with about 50.6 million people with irreversible blindness. This research presents how self-help devices for visually impaired are approach in recent years and proposes a new approach based on object recognition with deep learning. Through it, it is possible to perceive the trends in this line of research, how devices obtain information from the environment, how they interact with users, and other aspects — pointing essential factors to all those who research or wish to study this area.

In Proceedings of IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI 2019)
Fabrizzio Soares
Fabrizzio Soares
Associate Professor and CS Chair

Fabrizzio Soares is a professor of Computer Science, Information Systems and Software Engineering at INF/UFG. His research interests include Computer Vision, Human Computer Interaction, Machine Learning and Programming topics. He is the leader of the Pixellab group, which develops solutions for accesibilty, Precision Agriculture, and Interactive Systems.