Date of Award
6-6-2019
Document Type
Thesis - SCU Access Only
Publisher
Santa Clara : Santa Clara University, 2019
Department
Computer Engineering
First Advisor
Behnam Dezfouli
Abstract
Navigating while visually impaired is extremely difficult. Without sight, people must rely on their other senses to navigate through life, mainly by way of hearing and touching (with their cane). Nonetheless, these senses cannot completely make up for the loss of vision. In this paper, we propose NavSense, an assistive device that supplements existing technology, and improves navigation in day to day life. NavSense provides near real-time object identification and context to the user through auditory feedback. This paper describes the testing procedures used and results gathered while identifying the best components for the system. NavSense is capable of providing accurate results quickly on low cost and energy efficient edge devices.
Recommended Citation
Okazaki, Daniel; Dallow, Michael; and Ryan, John, "NavSense: Computer Vision for the Visually Impaired" (2019). Computer Science and Engineering Senior Theses. 146.
https://scholarcommons.scu.edu/cseng_senior/146