Depth-Vision Coordinated Robust Architecture for Obstacle Detection and Haptic Feedback

Abstract

The lightweight and low-cost 3-dimensional depth sensors have gained much attention in the computer vision and gaming industry. While its performance has been proven successful in the gaming industry, these sensors have not been utilized successfully for assistive devices. Leveraging on this gap, this paper presents the design, implementation, and evaluation of a depth-vision coordinated robust architecture for obstacle detection and haptic feedback system for the blind. The proposed system scans the scene in front, converts it into depth matrix, processes the information, to identify obstacles including physical objects and humans, and provide relevant haptic feedback for navigation of the blind. Through design and evaluation, the proposed system has shown to successfully identify objects and humans, perform real-time distance measurements, and provide a working solution.