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ORCID

https://orcid.org/0000-0001-5799-5596

Access Type

Campus-Only Access for One (1) Year

Document Type

thesis

Embargo Period

8-19-2020

Degree Program

Electrical & Computer Engineering

Degree Type

Master of Science in Electrical and Computer Engineering (M.S.E.C.E.)

Year Degree Awarded

2020

Month Degree Awarded

September

Abstract

This paper introduces a system which enables visually impaired users to detect objects and landmarks within the line of sight. The system works in two modes: landmark mode, which detects predefined landmarks, and object mode, which detects objects for everyday use. Users can get audio announcement for the name of the detected object or landmark as well as its estimated distances. Landmark detection helps visually impaired users explore an unfamiliar environment and build a mental map.

The proposed system utilizes a deep learning system for detection, which is deployed on the mobile phone and optimized to run in real-time. Unlike many other existing deep-learning systems that require an Internet connection or specific accessories. Our system works offline and only requires a smart phone with camera, which gives the advantage to avoid the cost for data services, reduce delay to access the cloud server, and increase the system reliability in all environments.

DOI

https://doi.org/10.7275/19015521

First Advisor

Aura Ganz

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