Agam Goyal, Ishaan Mahajan, Mihir Jagtap, Shivansh Aggarwal
Help People with Low-Vision to See Better in the World of Virtual Reality
According to WHO, around 2.2 billion people suffer from some kind of vision problems, making day-to-day life difficult in many situations. A major part to sense any kind of object, or an image is through vision. This is a major problem in our opinion, as it denies certain individuals equal opportunities, and also poses danger in some cases. For example, driving at night, for people with astigmatism might be risky in certain scenarios, or people having color blindness might not be able to distinguish colors of different fluids, in some cases distinguish blood discharge in certain fluids. Our software stack will help solve this problem, and mitigate the risks and potential hazards that come with certain vision problems. We plan to make this possible for everyone by providing tools and mechanisms to comprehend an image/object as clearly as possible, and if not possible in some scenarios, we tackle the problem through Optical Character Recognition, and by enabling text-to-speech.
With the advent of Virtual Reality (VR) and the world moving towards the Metaverse, we feel it is the need of the hour that there is a framework that enables low-vision people to see better in the virtual world, by combining the following techniques with the existing Virtual Reality stacks.
Increased luminance contrast is one of the most important factor for people with low-vision. We plan to enhance the difference between each pixel and the average of its adjacent pixels.
The most commonly used in vision enhancement to enable people with impaired vision to see details. The field of view of the camera is adjusted to adjust the magnification level.
Involves the conversion of images containing handwritten, typed, or printed text into machine-encoded text for ease of reading.
Integrating Text-to-Speech along with Optical Character Recognition (OCR) will help visually impaired people understand the written text without having to read it out.
Visit our GitHub repository for this project to view the codebase!
Click the link below to view our project presentation!