Student Work
Indoor Navigation for Blind Individuals Using Computer Vision & Machine Learning
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open in viewerNavigating the world with impaired vision is a challenging and hard-to-imagine task. To address this challenge, our team created a smartphone app that would alleviate struggles encountered when traversing indoor spaces. The app was created by utilizing a machine learning model, named D2GO, which helps to detect objects with the use of a smartphone camera. Using D2GO, our team was able to develop an app that can both detect and guide users around other people and obstacles within an indoor space. This app will serve as a framework for a navigational aid that can be further developed by future R&D teams.
- This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.
- Creator
- Subject
- Publisher
- Identifier
- 62966
- E-project-042022-170437
- Stichwort
- Award
- Advisor
- Year
- 2022
- Center
- Sponsor
- UN Sustainable Development Goals
- Date created
- 2022-04-20
- Resource type
- Source
- E-project-042022-170437
- Rights statement
- Zuletzt geändert
- 2023-11-30
Beziehungen
- In Collection:
Objekte
Artikel
Miniaturansicht | Titel | Sichtbarkeit | Embargo Release Date | Aktionen |
---|---|---|---|---|
Indoor_Navigation_for_Blind_Individuals_Using_Computer_Vision___Machine_Learning.pdf | Öffentlich | Herunterladen |
Permanent link to this page: https://digital.wpi.edu/show/hq37vr98g