Virtual Reality for the Visually Impaired

This thesis aims to illuminate and describe how there are problems with the development of virtual reality regarding visually impaired people. After discussing the reasons how and why this is a problem, this thesis will provide some possible solutions to develop virtual reality into a more user accessible technology, specifically for the visually impaired. As the popularity of virtual reality increases in digital culture, especially with Facebook announcing their development of Metaverse, there is a need for a future virtual reality environment that everyone can use. And it is in these early stages of development, that the need to address the problem of inaccessibility arises. As virtual reality is a relatively new medium in digital culture, the research on its use by visually impaired people has significant gaps. And as relatively few researchers are exploring this topic, my research will hopefully lead to more activity in this important area. Therefore, my research questions aim to address the current limitations of virtual reality, filling in some of the most significant gaps in this research area. My thesis will do this by conducting interviews and surveys to gather data that can further support and identify the crucial limitations of the visually impaired experience while trying to use virtual reality technology. The findings in this thesis will further address the problem, creating a possible solution and emphasizing the importance of user accessibility for the visually impaired in the future development of virtual reality. If digital companies and developers address this problem now, we can have a future where visually impaired people are treated more equally, with technologies developed specifically for them to experience virtual worlds.Master's Thesis in Digital CultureDIKULT350MAHF-DIKU

A new approach to image enhancement for the visually impaired

This works aims at enhancing images by using the colour appearance model CIECAM02 for the visually impaired to view digital displays to complement the existing image processing approaches with a reference to normal visions. Specifically, by studying the images perceived by low-vision users, the colour ranges of these perceived views are compared with those viewed by normal vision and then characterized and represented using CIECAM02 correlates, which include lightness, colourfulness, and hue. For low-vision users, the extents of these attributes are therefore obtained. Subsequently, for any input image, these CIECAM02 attributes are subsequently enhanced through histogram equalizer technique within their respective ranges for low-vision users. In comparison with the approach of RGB histogram equalizer, the preliminary result has shown that the proposed method appears to be better to enhance the contents depicted in an image. The evaluation experiment was carried out using an array of low-vision simulator glasses to be worn by a group of subjects with normal vision. The next stage of the work remains to invite real low-vision users to evaluate the proposed work.

A mobile image enhancement technology for visually impaired

In this thesis, an image enhancement application is developed for low-vision patients when they use iPhones to see images/watch videos. The thesis has two contributions. The first contribution is the new image enhancement algorithm which combines human vision features. The new image enhancement algorithm is modified from a wavelet transform based image enhancement algorithm developed by Dr. Jinshan Tang. Different from the original algorithm, the new image enhancement algorithm combines human visual feature into the algorithm and thus can make the new algorithm more effective. Experimental simulation results show that the proposed algorithm has better visual results than the algorithm without combining visual features. The second contribution of this thesis is the development of a mobile image enhancement application. In this application, users with low-vision can see clearer images on an iPhone which is installed with the application I have developed

A smart yoga mat system designed for visually impaired people

Globally, nearly 2.2 billion people are visually impaired, while 39 million are blind at present. Due to various factors, it is difficult for the blind to exercise. Though associations for blind people and disabled schools provide more possibilities for sports training for visually impaired people, these resources cannot reach everyone in need because of location and foundation limits. The project aims to make fitness more accessible for visually impaired people to help them keep healthy. Thus it could support their confidence and independence as they expected. Furthermore, society\u27s awareness of visually impaired people\u27s difficulties while exercising then, more studies could be built on the accessibility of fitness equipment for more feasible solutions in the near future. A smart yoga mat that used Somatosensory technology and the tactile response was designed to reach this aim. Qualitative interviews, Wizard of Oz, prototype testing, and other design methods were used to test the design\u27s usability

Accessibility-based reranking in multimedia search engines

Traditional multimedia search engines retrieve results based mostly on the query submitted by the user, or using a log of previous searches to provide personalized results, while not considering the accessibility of the results for users with vision or other types of impairments. In this paper, a novel approach is presented which incorporates the accessibility of images for users with various vision impairments, such as color blindness, cataract and glaucoma, in order to rerank the results of an image search engine. The accessibility of individual images is measured through the use of vision simulation filters. Multi-objective optimization techniques utilizing the image accessibility scores are used to handle users with multiple vision impairments, while the impairment profile of a specific user is used to select one from the Pareto-optimal solutions. The proposed approach has been tested with two image datasets, using both simulated and real impaired users, and the results verify its applicability. Although the proposed method has been used for vision accessibility-based reranking, it can also be extended for other types of personalization context

Image quality loss and compensation for visually impaired observers

The measurement and modeling of image quality are aimed to assist the design and optimization of systems, typically built for ‘normal’ observer vision. But in reality image viewers rarely have perfect vision. There have been few attempts and no universal framework for measuring image quality loss due to visual impairments. The paper presents initial experiments designed to measure still image quality losses, as experienced by observers with visual accommodation problems, by proposing modifications to the Quality Ruler method described in ISO 20462-3:2012. A simple method is then presented, which compensates directly on the display for some of the quality lost due to the impairment. It uses a purpose-built image equalization software. The compensated image is finally examined in terms of quality gained. The losses and gains in image quality are measured on a Standard Quality Scale (SQS), where one unit corresponds to 1 JND. Initial results show that the quality lost due to visual accommodation impairments can be accurately measured with the modified ruler method. The loss is scene-dependent. Partial or full quality compensation can be achieved for such impairments, using image contrast equalization; the level of quality gained also scenedependent

Ability of head-mounted display technology to improve mobility in people with low vision: a systematic review

Purpose: The purpose of this study was to undertake a systematic literature review on how vision enhancements, implemented using head-mounted displays (HMDs), can improve mobility, orientation, and associated aspects of visual function in people with low vision. Methods: The databases Medline, Chinl, Scopus, and Web of Science were searched for potentially relevant studies. Publications from all years until November 2018 were identified based on predefined inclusion and exclusion criteria. The data were tabulated and synthesized to produce a systematic review. Results: The search identified 28 relevant papers describing the performance of vision enhancement techniques on mobility and associated visual tasks. Simplifying visual scenes improved obstacle detection and object recognition but decreased walking speed. Minification techniques increased the size of the visual field by 3 to 5 times and improved visual search performance. However, the impact of minification on mobility has not been studied extensively. Clinical trials with commercially available devices recorded poor results relative to conventional aids. Conclusions: The effects of current vision enhancements using HMDs are mixed. They appear to reduce mobility efficiency but improved obstacle detection and object recognition. The review highlights the lack of controlled studies with robust study designs. To support the evidence base, well-designed trials with larger sample sizes that represent different types of impairments and real-life scenarios are required. Future work should focus on identifying the needs of people with different types of vision impairment and providing targeted enhancements. Translational Relevance: This literature review examines the evidence regarding the ability of HMD technology to improve mobility in people with sight loss