MR.NAVI: Mixed-Reality Navigation Assistant for the Visually Impaired
This addresses a critical problem for over 43 million people with severe visual impairment by improving their ability to navigate unfamiliar environments, though it appears incremental as it builds on existing computer vision and NLP methods.
The paper tackles navigation challenges for visually impaired individuals by introducing MR.NAVI, a mixed reality system that uses real-time scene understanding and audio feedback to enhance spatial awareness, showing promising usability and effectiveness in user studies.
Over 43 million people worldwide live with severe visual impairment, facing significant challenges in navigating unfamiliar environments. We present MR.NAVI, a mixed reality system that enhances spatial awareness for visually impaired users through real-time scene understanding and intuitive audio feedback. Our system combines computer vision algorithms for object detection and depth estimation with natural language processing to provide contextual scene descriptions, proactive collision avoidance, and navigation instructions. The distributed architecture processes sensor data through MobileNet for object detection and employs RANSAC-based floor detection with DBSCAN clustering for obstacle avoidance. Integration with public transit APIs enables navigation with public transportation directions. Through our experiments with user studies, we evaluated both scene description and navigation functionalities in unfamiliar environments, showing promising usability and effectiveness.