Research Project
Object Recognition and Interpretation for Visually Impaired Assistance
(Perceptual Augmentation: Object Recognition and Interpretation for Visually Impaired Assistance)
Research Team
Lead Researchers:
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Dr. Abhishek Verma, Computer Science
Collaborators:
Student Team:
- Gurnoor Kaur, BS Computer Science
- Kate Hagen, BS Computer Science
- Manuel Negrete, BS Computer Science
- Edward Shatverov, BS Computer Science
- S Abrar Nizam, BS Computer Science
Funding
- Funding Organization:
- Funding Program:
SYNOPSIS
- This research focuses on designing and implementing the Vision Assist mobile app to help visually impaired people by recognizing objects and reading text aloud.
- It uses a phone’s camera and machine learning to give real-time voice feedback for easier navigation of surroundings.
- The app also includes GPS directions and an emergency alarm for added safety.
Research Questions and Research Objectives
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Develop an assistive technology solution that improves the independence of visually impaired users through object detection and text interpretation.
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Enhance real-time environment awareness using a smartphone’s camera and machine learning algorithms.
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Implement a user-friendly, accessible interface that provides clear voice feedback for navigation and object recognition.
Research Methods
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Conducted interviews with visually impaired individuals to learn about their daily navigation challenges.
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Used the YOLO machine learning model to accurately identify objects in the environment.
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Employed Google Cloud API to convert text into clear speech for users.
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Integrated GPS navigation with Apple Maps to provide real-time voice directions.
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Added an emergency alarm feature that connects users to their emergency contacts using Twilio.
Research Results and Deliverables
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Developed a functional prototype that effectively identifies objects and reads text.
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Integrated voice-guided GPS navigation for enhanced user independence.
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Implemented an emergency alarm feature to ensure user safety.
Commercialization and/or Societal Impact Opportunities
- Application: Launch the app as a vital tool for visually impaired individuals.
- Key Value: Increases independence and enhances safety in everyday situations.
- Potential Users: Visually impaired individuals, organizations focused on accessibility
Research Timeline
Start Date:
End Date:
Lead Researchers:
-
Dr. Abhishek Verma, Computer Science
Collaborators:
Student Team:
- Gurnoor Kaur, BS Computer Science
- Kate Hagen, BS Computer Science
- Manuel Negrete, BS Computer Science
- Edward Shatverov, BS Computer Science
- S Abrar Nizam, BS Computer Science
Funding
- Funding Organization:
- Funding Program: