Authors:
Antonio Miguel Batista Dourado
1
and
Emerson Carlos Pedrino
2
Affiliations:
1
Federal University of São Carlos and Federal Institute of São Paulo - Boituva Campus, Brazil
;
2
Federal University of São Carlos, Brazil
Keyword(s):
Visually Impaired People, Electronic Travel Aids, Computer Vision System, Navigation System, Object Recognition, Object Classification.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Image and Video Analysis
;
Motion, Tracking and Stereo Vision
;
Pattern Recognition
;
Robotics
;
Segmentation and Grouping
;
Software Engineering
;
Tracking and Visual Navigation
Abstract:
Loss of vision has a large detrimental impact on a person’s mobility. Every day, visually impaired people
(VIPs) face various challenges just to get around in the most diverse environments. Technological solutions,
called Electronic Travel Aids, help a VIP with these challenges, giving greater confidence in the task of getting
around in unfamiliar surroundings. Thus, this article presents an embedded navigation and classification
system for helping VIPs indoors. Using stereo vision, the system is able to detect obstacles and choose
safe ways for the VIP to walk around without colliding. A convolutional neural network using a graphics
processing unit (GPU) classifies the obstacles. Acoustic feedback is transmitted to the VIP. The article also
features a wearable prototype, to which the system hardware is docked for use. Using the system, the prototype
could detect and classify obstacles in real time defining free paths, all with battery autonomy of about 6 hours.