A Hazard Detection and Tracking System for People with Peripheral Vision Loss using Smart Glasses and Augmented Reality

Abstract

Peripheral vision loss is the lack of ability to recognise objects and shapes in the outer area of the visual field. This condition can affect people’s daily activities and reduces their quality of life. In this work, a smart technology that implements computer vision algorithms in real-time to detect and track moving hazards around people with peripheral vision loss is presented. Using smart glasses, the system processes real-time captured video and produces warning notifications based on predefined hazard danger levels. Unlike other obstacle avoidance systems, this system can track moving objects in real-time and classify them based on their motion features (such as speed, direction, and size) to display early warning notification. A moving camera motion compensation method was used to overcome artificial motions caused by camera movement before an object detection phase. The detected moving objects were tracked to extract motion features which were used to check if the moving object is a hazard or not. A detection system for camera motion states was implemented and tested on real street videos as the first step before an object detection phase. This system shows promising results in motion detection, motion tracking, and camera motion detection phases. Initial tests have been carried out on Epson’s smart glasses to evaluate the real-time performance for this system. The proposed system will be implemented as an assistive technology that can be used in daily life.