Abstract
In this paper, we present a system that allows visually impaired people to autonomously navigate in an unknown indoor and outdoor environment. The system, explicitly designed for low vision people, can be generalized to other users in an easy way. We assume that special landmarks are posed for helping the users in the localization of pre-defined paths. Our novel approach exploits the use of both the inertial sensors and the camera integrated into the smartphone as sensors. Such a navigation system can also provide direction estimates to the tracking system to the users. The success of out approach is proved both through experimental tests performed in controlled indoor environments and in real outdoor installations. A comparison with deep learning methods has been presented.
Highlights
The possibility of exploiting Information and Communication Technologies (ICT) for supporting Visually Impaired People (VIP) and promoting vision substitution has been widely considered over the last five decades, especially with the emergence of electronic Braille displays, synthetic speech and ultrasonic sensors
We explored the performance improvements of Pedestrian Dead Reckoning (PDR) schemes that can be enabled by the exploitation of suitable Computer Vision (CV) functions, devised to provide additional heading and velocity measurements
The main contributions of the paper are the following: i) demonstrating how the camera sensors can be exploited for providing measurements similar to the ones provided by the IMU (Inertial Measurement Unit) systems and characterizing the errors of these measurements; ii) quantifying the complexity of the processing required by the computer vision algorithms and discussing the best trade-offs between energy consumption and measurement availability and comparing it with deep learning solutions; iii) designing a tracking system based on the integration of IMU and camera-based measurements and evaluating its accuracy in experiments with real users
Summary
The possibility of exploiting Information and Communication Technologies (ICT) for supporting Visually Impaired People (VIP) and promoting vision substitution has been widely considered over the last five decades, especially with the emergence of electronic Braille displays, synthetic speech and ultrasonic sensors. The main contributions of the paper are the following: i) demonstrating how the camera sensors can be exploited for providing measurements similar to the ones provided by the IMU (Inertial Measurement Unit) systems and characterizing the errors of these measurements; ii) quantifying the complexity of the processing required by the computer vision algorithms and discussing the best trade-offs between energy consumption and measurement availability and comparing it with deep learning solutions; iii) designing a tracking system based on the integration of IMU and camera-based measurements and evaluating its accuracy in experiments with real users.
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