Abstract Independent travel is a well-known challenge for blind and visually impaired persons. In this paper, we propose a proof-of-concept computer vision-based wayfinding aid for blind people to independently access unfamiliar indoor environments. In order to find different rooms (e.g. an office, a laboratory, or a bathroom) and other building amenities (e.g. an exit or an elevator), we incorporate object detection with text recognition. First, we develop a robust and efficient algorithm to detect doors, elevators, and cabinets based on their general geometric shape, by combining edges and corners. The algorithm is general enough to handle large intraclass variations of objects with different appearances among different indoor environments, as well as small inter-class differences between different objects such as doors and doorlike cabinets. Next, to distinguish intra-class objects (e.g. an office door from a bathroom door), we extract and recognize text information associated with the detected objects.
Similarly, a robust and efficient algorithm is developed in REF to detect doors, elevators and cabinets from images.
Toward a computer vision-based wayfinding aid for blind persons to access unfamiliar indoor environments
Machine Vision and Applications
Machine Vision and Applications
Medicine Computer Science