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Toward a Computer Vision-based Wayfinding Aid for Blind Persons to Access Unfamiliar Indoor Environments
Yingli Tian1, Xiaodong Yang, Chucai Yi
1Electrical Engineering Department, The City College, and Graduate Center, City University of New York, New York, NY 10031.
Machine Vision and Applications
|May 1, 2013
Summary
This study introduces a computer vision system to help blind individuals navigate indoor spaces. The system uses object detection and text recognition to identify rooms and amenities, providing audio feedback for independent travel.
Area of Science:
- Computer Vision
- Assistive Technology
- Human-Computer Interaction
Background:
- Independent travel presents significant challenges for blind and visually impaired individuals, particularly in unfamiliar indoor environments.
- Existing wayfinding solutions often lack the sophistication to handle the complexities of diverse indoor settings.
Purpose of the Study:
- To develop and demonstrate a proof-of-concept computer vision-based wayfinding aid for enhancing independent navigation for blind persons.
- To integrate object detection and text recognition for identifying indoor spaces and amenities.
Main Methods:
- A robust algorithm was developed for detecting doors, elevators, and cabinets using geometric features (edges and corners).
- Text recognition was employed to differentiate between similar objects (e.g., office vs. bathroom doors) by analyzing associated signage.
- Optical character recognition (OCR) software was utilized after text region extraction and background interference filtering.
Main Results:
- The system successfully detects key indoor features like doors and elevators.
- Text recognition accurately distinguishes between objects with similar appearances but different functions.
- Integrated information (object type, location, text) is presented to the user via speech output.
Conclusions:
- The proposed computer vision system offers a promising approach to improve independent indoor navigation for the visually impaired.
- Combining geometric object detection with OCR-based text recognition provides a comprehensive wayfinding solution.
- This technology has the potential to significantly enhance accessibility in public and private indoor environments.
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