Improve accessibility for Low Vision and Blind people using Machine Learning and Computer Vision
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866911820008128512 |
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| author | Shukurov, Jasur |
| author_facet | Shukurov, Jasur |
| contents | With the ever-growing expansion of mobile technology worldwide, there is an increasing need for accommodation for those who are disabled. This project explores how machine learning and computer vision could be utilized to improve accessibility for people with visual impairments. There have been many attempts to develop various software that would improve accessibility in the day-to-day lives of blind people. However, applications on the market have low accuracy and only provide audio feedback. This project will concentrate on building a mobile application that helps blind people to orient in space by receiving audio and haptic feedback, e.g. vibrations, about their surroundings in real-time. The mobile application will have 3 main features. The initial feature is scanning text from the camera and reading it to a user. This feature can be used on paper with text, in the environment, and on road signs. The second feature is detecting objects around the user, and providing audio feedback about those objects. It also includes providing the description of the objects and their location, and giving haptic feedback if the user is too close to an object. The last feature is currency detection which provides a total amount of currency value to the user via the camera. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2404_00043 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Improve accessibility for Low Vision and Blind people using Machine Learning and Computer Vision Shukurov, Jasur Human-Computer Interaction Computer Vision and Pattern Recognition Machine Learning With the ever-growing expansion of mobile technology worldwide, there is an increasing need for accommodation for those who are disabled. This project explores how machine learning and computer vision could be utilized to improve accessibility for people with visual impairments. There have been many attempts to develop various software that would improve accessibility in the day-to-day lives of blind people. However, applications on the market have low accuracy and only provide audio feedback. This project will concentrate on building a mobile application that helps blind people to orient in space by receiving audio and haptic feedback, e.g. vibrations, about their surroundings in real-time. The mobile application will have 3 main features. The initial feature is scanning text from the camera and reading it to a user. This feature can be used on paper with text, in the environment, and on road signs. The second feature is detecting objects around the user, and providing audio feedback about those objects. It also includes providing the description of the objects and their location, and giving haptic feedback if the user is too close to an object. The last feature is currency detection which provides a total amount of currency value to the user via the camera. |
| title | Improve accessibility for Low Vision and Blind people using Machine Learning and Computer Vision |
| topic | Human-Computer Interaction Computer Vision and Pattern Recognition Machine Learning |
| url | https://arxiv.org/abs/2404.00043 |