EYECane

Abstract

We demonstrate a novel assistive device which can help the visually impaired or blind people to gain more safe mobility, which is called as "EYECane". The EYECane is the white-cane with embedding a camera and a computer. It automatically detects obstacles and recommends some avoidable paths to the user through acoustic interface. For this, it is performed by three steps: Firstly, it extracts obstacles from image streaming using online background estimation, thereafter generates the occupancy grid map, which is given to neural network. Finally, the system notifies a user of an paths recommended by machine learning. To assess the effectiveness of the proposed EYECane, it was tested with 5 users and the results show that it can support more safe navigation, and diminish the practice and efforts to be adept in using the white cane.