HEAD-MOUNTED MOBILITY AID FOR LOW VISION USING SCENE CLASSIFICATION TECHNIQUES
Résumé
This paper describes a new mobility aid for people with
severe visual impairments which combines technology from
the field of virtual reality with advanced computer vision
techniques. A neural-network classifier is used to identify
objects in images from a head mounted camera so that scene
content specifically important for mobility may be made
more visible. Enhanced images are displayed to the user on
a head mounted display using a high saturation colour
scheme where each type of object has a different colour,
resulting in images which are highly visible and easy to
interpret. The object classifier achieves a level of accuracy
over 90%. Results from a pilot study conducted using
people with a range of visual impairments are presented in
which performance on a difficult mobility-related task was
improved by over 100% using the system.