Seeing Without Sight - An Automatic Cognition System Dedicated to Blind and Visually Impaired People

Ruxandra Tapu, Bogdan Mocanu, Titus Zaharia; Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2017, pp. 1452-1459

Abstract


In this paper we present an automatic cognition system, based on computer vision algorithms and convolutional neural networks, designed to assist the visually impaired users during navigation in highly dynamic urban scenes. A first feature concerns the real-time detection of various types of objects existent in the outdoor environment relevant from the perspective of a VI person. The objects are followed between successive frames using a novel tracker, which exploits an offline trained neural-network and is able to track generic objects using motion patterns and visual attention models. The system is able to handle occlusions, sudden camera/object movements, rotation or various complex changes. Finally, an object classification module is proposed with new categories specific to assistive devices applications. The experimental evaluation, performed on the VOT 2016 dataset and on a set of videos acquired with the help of VI users, demonstrates the effectiveness of the proposed method.

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[bibtex]
@InProceedings{Tapu_2017_ICCV,
author = {Tapu, Ruxandra and Mocanu, Bogdan and Zaharia, Titus},
title = {Seeing Without Sight - An Automatic Cognition System Dedicated to Blind and Visually Impaired People},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV) Workshops},
month = {Oct},
year = {2017}
}