Design workshops are often inaccessible to blind people due to a strong reliance on visual design methods. This paper presents an adapted low-fidelity prototyping method to enable blind persons to actively participate in the early design stages of developing assistive devices. We chose the development of a 2D tactile display as a case study. Therefore, we conducted four workshops with blind participants to develop a haptic toolkit and adapt the structure of prototyping workshops based on the preferences of the target group. The resulting toolkit and workshop structure were applied in six prototyping workshops with 12 blind participants to design a new 2D tactile display to test the new method. Our findings show that the participation of blind individuals is highly relevant for structuring accessible prototyping workshops, deciding group size, and developing accessible prototyping materials. Furthermore, our work lays the foundation for further investigation of the role of sighted assistants and the design of workshops that truly center blind persons as primary contributors.

In a world driven by data visualization, ensuring the inclusive accessibility of charts for Blind and Visually Impaired (BVI) individuals remains a significant challenge. Charts are usually presented as raster graphics without textual and visual metadata needed for an equivalent exploration experience for BVI people. Additionally, converting these charts into accessible formats requires considerable effort from sighted individuals. Digitizing charts with metadata extraction is just one aspect of the issue; transforming it into accessible modalities, such as tactile graphics, presents another difficulty. To address these disparities, we propose Chart4Blind, an intelligent user interface that converts bitmap image representations of line charts into universally accessible formats. Chart4Blind achieves this transformation by generating Scalable Vector Graphics (SVG), Comma-Separated Values (CSV), and alternative text exports, all comply with established accessibility standards. Through interviews and a formal user study, we demonstrate that even inexperienced sighted users can make charts accessible in an average of 4 minutes using Chart4Blind, achieving a System Usability Scale rating of 90%. In comparison to existing approaches, Chart4Blind provides a comprehensive solution, generating end-to-end accessible SVGs suitable for assistive technologies such as embossed prints (papers and laser cut), 2D tactile displays, and screen readers. For additional information, including open-source codes and demos, please visit our project page https://moured.github.io/chart4blind/.

Structured Visual Content (SVC) such as graphs, flow charts, or the like are used by authors to illustrate various concepts. While such depictions allow the average reader to better understand the contents, images containing SVCs are typically not machine-readable. This, in turn, not only hinders automated knowledge aggregation, but also the perception of displayed information for visually impaired people. In this work, we propose a synthetic dataset, containing SVCs in the form of images as well as ground truths. We show the usage of this dataset by an application that automatically extracts a graph representation from an SVC image. This is done by training a model via common supervised learning methods. As there currently exist no large-scale public datasets for the detailed analysis of SVC, we propose the Synthetic SVC (SSVC) dataset comprising 12,000 images with respective bounding box annotations and detailed graph representations. Our dataset enables the development of strong models for the interpretation of SVCs while skipping the time-consuming dense data annotation.We evaluate our model on both synthetic and manually annotated data and show the transferability of synthetic to real via various metrics, given the presented application. Here, we evaluate that this proof of concept is possible to some extend and lay down a solid baseline for this task. We discuss the limitations of our approach for further improvements. Our utilized metrics can be used as a tool for future comparisons in this domain. To enable further research on this task, the dataset is publicly available at https://bit.ly/3jN1pJJ.

Technological advances enable the development of new low vision aids. One such new technology is virtual reality (VR). Existing VR applications offer a variety of adjustments to the content and the user's environment to support people with low vision. Yet, an interaction concept to conveniently activate and control these aids is missing. Therefore, we designed and implemented an interaction concept based on user and expert feedback and evaluated it in a user study. Our application offers various aids to support residual vision and a radial menu for intuitive use of these aids. The results of the user study show that the VR application allows simple task solving comparable to a desktop computer. Furthermore, the user study gives an insight into the effects of different visual impairments on the usage of VR, since the field of view has a larger impact than visual acuity. Overall, our results indicate that VR is a suitable aid to support the individual needs of users with low vision.

A lot of information is nowadays presented graphically. However, students with blindness do not have access to visual information. Providing an alternative text is not always the appropriate solution as exploring graphics to discover information independently is a fundamental part of the learning process. In this work, we introduce a mobile audio-tactile learning environment, which facilitates the incorporation of real educational material. We evaluate our system by comparing three methods of interaction with tactile graphics: A tactile graphic augmented by (1) a document with key index information in Braille, (2) a digital document with key index information and (3) the TPad system, an audio-tactile solution meeting the specific needs within the school context. Our study shows that the TPad system is suitable for educational environments. Moreover, compared to the other methods TPad is faster to explore tactile graphics and it suggests a promising effect on the memorization of information.