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End-to-End Indoor Navigation Assistance for the Visually Impaired Using Monocular Camera

conference contribution
posted on 2019-01-16, 00:00 authored by K Saleh, R A Zeineldin, Mohammed Hossny, Saeid Nahavandi, N El-Fishawy
© 2018 IEEE. In this work a novel approach for the problem of indoor navigation assistance for the visually impaired people is proposed based solely on a monocular camera. In our formulation for the problem, we cast it as an image classification problem and tackle it holistically in an end-to-end fashion via state-of-the-art deep convolutional residual networks. Given an input RGB image of an indoor scene, our model can accurately guide the visually impaired people to navigate around the obstacles in the scene using four discrete navigational directions. Our model has achieved resilient results in terms of higher classification accuracies with a lower rate of false alarms. Moreover, we compared the performance of our model against two baseline approaches and it has outperformed them with more than 25% improvements with respect to the F1 measure evaluation score.

History

Event

Systems, Man, and Cybernetics. Conference (2018 : Miyazaki, Japan)

Pagination

3504 - 3510

Publisher

IEEE

Location

Miyazaki, Japan

Place of publication

Piscataway, N.J.

Start date

2018-10-07

End date

2018-10-10

ISBN-13

9781538666500

Language

eng

Publication classification

E1 Full written paper - refereed

Title of proceedings

SMC 2018 : Proceedings of the 2018 IEEE International Conference on Systems, Man, and Cybernetics