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MIRA Wins OpenCV Spatial AI Competition

Vision System For Visually Impaired by Jagadish Mahendran



Our mission is to provide a reliable smart perception system to assist blind and visually impaired people to safely ambulate in a variety of indoor and outdoor environments using an OAK-D sensor. In this project, the team has developed a comprehensive vision system for visually impaired people for indoor and outdoor navigation, along with scene understanding. The developed system is simple, fashionable and is not noticeable as an assistive device. Common challenges such as traffic signs, hanging obstacles, crosswalk detection, moving obstacles, and elevation changes (e.g., staircase detection, curb entry/exits), and localization are addressed using advanced perception tasks that can be run on low computing power. A convenient, user-friendly voice interface allows users to control and interact with the system. After conducting hours of testing in Monrovia, California, downtown and neighboring areas, we are confident that this project addresses common challenges faced by visually impaired people. Motivation for the project Back in 2013 as I started my Master’s in Artificial Intelligence, the idea of developing a visual assistance system first occured to me. I had even shared a proposal with a professor. The infeasibility of using smart sensors then, combined with deep learning techniques and edge AI not being mainstream in computer vision made it difficult to make any progress on this project. I have been an AI Engineer for the past 5 years. Earlier this year when I met my visually impaired friend Breean Cox, I was struck by the irony that while I have been teaching robots to see, there are many people who cannot see and need help. This further motivated me to build the visual assistance system. The timing of the OpenCV Spatial AI competition could not have been better, it was the perfect channel for me to build this system and bring this idea to life.

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