Improve the Accessibility of Tactile Charts

Engel, Christin; Weber, Gerhard

doi:10.1007/978-3-319-67744-6_12

Cited by 18 publications

(10 citation statements)

References 13 publications

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“…Different textures represent the colour information and labels. Engel et al [50] proposed improved guidelines for charts and studied how design can improve the readability of tactile charts. Research towards developing tactile graphs is advancing as in [50]- [52].…”

Section: Methods For Identifying Chartsmentioning

confidence: 99%

Towards Assisting the Visually Impaired: A Review on Techniques for Decoding the Visual Data From Chart Images

Shahira

Lijiya

2021

IEEE Access

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The textual data of a document is supplemented by the graphical information in it. To make communication easier, they contain tables, charts and images. However, it excludes a section of our population -the visually impaired. With technological advancements, the blind can access the documents through text to speech software solutions. In this method, even images can be conveyed by reading out the figure captions. However, charts and other statistical comparisons which involve critical information are difficult to be "read" out this way. Aim of this paper is to analyse various methods available to solve this vexatious issue. We survey the state-of-the-art works that do the exact opposite of graphing tools. In this paper, we explore the existing literature in understanding the graphs and extracting the visual encoding from them. We classify these approaches into modality-based approaches, conventional and deep-learning based methods. The survey also contains comparisons and analyses relevant study datasets. As an outcome of this survey, we observe that: (i) All existing works under each category need decoding in a variety of graphs. (ii) Among the approaches, deep learning performs remarkably well in localisation and classification. However, it needs further improvements in reasoning from chart images. (iii) Research works are still in progress to access data from vector images. Recreating data from the raster images has unresolved issues. Based on this study, the various applications of decoding the graphs, challenges and future possibilities are also discussed. This paper explores current works in the extraction of chart data, which seek to enable researchers in Human Computer Interaction to achieve human-level perception of visual data by machines. In this era of visual summarisation of data, the AI approaches can automate the underlying data extraction and hence provide the natural language descriptions to support visually disabled users.

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Section: Methods For Identifying Chartsmentioning

confidence: 99%

Towards Assisting the Visually Impaired: A Review on Techniques for Decoding the Visual Data From Chart Images

Shahira

Lijiya

2021

IEEE Access

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“…Tactile perception mainly utilizes tactile graphics such as embossed prints and physical visualization (19/56), haptic feedback such as forced vibrations (15/56), and braille for texts (7/56). For many visually impaired users, perceiving information through touch is common, particularly in an educational context [EW17b], and its spatiality allows simultaneous and on-demand exploration of data trends in contrast to linear audio [EW18]. However, it requires motor movement and lacks the bandwidth to support the preattentive processing of multiple elements in a visualization.…”

Section: Sensory Modalitymentioning

confidence: 99%

“…In tactile graphics, heavy guidelines (e.g., grids) can hamper the efficient perception of data, as with overwhelming content and ambiguous textures that are used in place of color [EW17b, EW17a, YMB * 20]. Grasping a chart's orientation is also crucial for a visually impaired user to successfully understand the visualization [EW17b]. Braille labels are usually accompanied to convey precise values and textual elements such as legends.…”

Section: Sensory Modalitymentioning

confidence: 99%

Accessible Visualization: Design Space, Opportunities, and Challenges

Kim

Joyner

Riegelhuth

et al. 2021

Computer Graphics Forum

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Visualizations are now widely used across disciplines to understand and communicate data. The benefit of visualizations lies in leveraging our natural visual perception. However, the sole dependency on vision can produce unintended discrimination against people with visual impairments. While the visualization field has seen enormous growth in recent years, supporting people with disabilities is much less explored. In this work, we examine approaches to support this marginalized user group, focusing on visual disabilities. We collected and analyzed papers published for the last 20 years on visualization accessibility. We mapped a design space for accessible visualization that includes seven dimensions: user group, literacy task, chart type, interaction, information granularity, sensory modality, assistive technology. We described the current knowledge gap in light of the latest advances in visualization and presented a preliminary accessibility model by synthesizing findings from existing research. Finally, we reflected on the dimensions and discussed opportunities and challenges for future research.

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“…Data sonification has been used on various visualizations such as line graphs, bar graphs, and maps [90,24,42]. Tactile visualizations realized via haptic feedback, braille display, or embossed prints are another popular approach to enhance accessibility for people with visual impairments [83,27,30,28,29,61,89,33,43,26]. Yet, the low-resolution nature of tactile visualizations limits their use for more complex visualizations [29].…”

Section: Visualization Accessibility For Visually Impaired Peoplementioning

confidence: 99%

“…Tactile visualizations realized via haptic feedback, braille display, or embossed prints are another popular approach to enhance accessibility for people with visual impairments [83,27,30,28,29,61,89,33,43,26]. Yet, the low-resolution nature of tactile visualizations limits their use for more complex visualizations [29]. Another recent exploration suggests that olfaction can be use to perceive data [62].…”

Section: Visualization Accessibility For Visually Impaired Peoplementioning

confidence: 99%

Communicating Visualizations without Visuals: Investigation of Visualization Alternative Text for People with Visual Impairments

Jung¹,

Mehta²,

Kulkarni³

et al. 2021

Preprint

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Alternative text is critical in communicating graphics to people who are blind or have low vision. Especially for graphics that contain rich information, such as visualizations, poorly written or an absence of alternative texts can worsen the information access inequality for people with visual impairments. In this work, we consolidate existing guidelines and survey current practices to inspect to what extent current practices and recommendations are aligned. Then, to gain more insight into what people want in visualization alternative texts, we interviewed 22 people with visual impairments regarding their experience with visualizations and their information needs in alternative texts. The study findings suggest that participants actively try to construct an image of visualizations in their head while listening to alternative texts and wish to carry out visualization tasks (e.g., retrieve specific values) as sighted viewers would.The study also provides ample support for the need to reference the underlying data instead of visual elements to reduce users' cognitive burden. Informed by the study, we provide a set of recommendations to compose an informative alternative text.

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Improve the Accessibility of Tactile Charts

Cited by 18 publications

References 13 publications

Towards Assisting the Visually Impaired: A Review on Techniques for Decoding the Visual Data From Chart Images

Towards Assisting the Visually Impaired: A Review on Techniques for Decoding the Visual Data From Chart Images

Accessible Visualization: Design Space, Opportunities, and Challenges

Communicating Visualizations without Visuals: Investigation of Visualization Alternative Text for People with Visual Impairments

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