Augmented reality for the sight impaired

Vision loss is rarely absolute; most people referred to as blind have some form of residual vision. This residual vision can create a confusing view of the world. In this thesis, I explore how a camera system and a wearable display can augment an image of the word to improve its visibility and understanding to a visually impaired wearer. I focus on two crucial parts of life; recognising faces and reading. In the first part of this thesis, I design and validate a new face perception test to assess different image enhancement forms. I used this new test to measure the impact of image enhancement on a visually impaired population (n=64). The results found that approximately 40% of participants showed a significant improvement in test scores. Performance was related to reading acuity and lower spatial frequency loss. I then develop and integrate a complete real-time image processing solution for face perception enhancement with an augmented reality display, demonstrating a practical application of the image enhancements. The second part of this thesis's focus is reading. I compare paper-based reading performance against reading with a virtual reality (VR) display with a visually impaired population (n=53). I further assess the impact of different colours on reading with the VR display. The results found no difference in reading performance, comparing VR to paper- based. The colour of text and background had a significant effect, with 75% of participants having a preferred colour combination. A participant with a higher overall magnitude of colour vision loss is more likely to benefit from white text on a black background than black text on a yellow background. Augmenting an individual's residual vision can improve the quality of information they receive about the visual world. While not universal, this improvement has the potential to enhance a visually impaired person's quality of life significantly.