Team, Visitors, External Collaborators
Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
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Section: New Results

High tech vision aid-systems for low-vision patients

Multilayered Analysis of Newspaper Structure and Design

Participants : Hui-Yin Wu, Pierre Kornprobst.

The understanding of newspaper document structure can help in the adaptation of text and visual content for different devices and media [53], as well as, in the context of low vision, to enhance accessibility by combining magnification and text-to-speech aids. However, automated segmentation of complex document structures like newspapers remains an ongoing challenge due its dense layout with numerous visual and textual design elements [38], [44].

To address this challenge, we propose a multi-layered analysis of structure and design, presented in [27]. Taking images of newspaper front pages as input, our approach uses a combination of computer vision techniques to segment newspapers with complex layouts into meaningful blocks of varying degrees of granularity, and convolutional neural network (CNN) to classify each block. The final output presents a visualization of the various design elements present in the newspaper such as in Figure 2. Compared to previous approaches, our method introduces a much larger set of design-related labels (23 labels against less than 10 before) resulting in a very fine description of the pages, with high accuracy (83%), as shown in Figure 3.

Figure 2. Visualization of the classification results on three different newspapers in our test set. Colors indicate primary categories as masthead elements (purple), text column (gray), ads (blue), images (brown) and minor text elements (green). Original images copyright of (from left to right) New York Times, 20 Minutes, and DeMorgan, courtesy of Newseum.
Figure 3. Classification result per categories. Results are presented in the table, showing the number of design elements that are correctly classified, false-negative (i.e. missing label), and false-positive (i.e. wrongly assigned label). Then a red chart shows the errors together with the number of segments (black line) used for the test dataset. To the right, the grey curve indicates the number of segments which were available in the training set.

This work is presented in [27].

Towards accessible news reading design in virtual reality for low vision

Participants : Hui-Yin Wu, Aurélie Calabrèse, Pierre Kornprobst.

Low-vision conditions resulting in partial loss of the visual field strongly affect patients’ daily tasks and routines, and none more prominently than the ability to access text. Though vision aids such as magnifiers, digital screens, and text-to-speech devices can improve overall accessibility to text, news media, which is non-linear and has complex and volatile formatting, bars low-vision patients from easy access to essential news content [54].

Our aim is to position virtual reality as the next step towards accessible and enjoyable news reading for the low vision. Our ongoing work, which we present in [26], consists of an extensive review into existing research on low-vision reading technologies and accessibility for modern news media. From previous research and studies, we then conduct an analysis into the advantages of virtual reality for low-vision reading and propose comprehensive guidelines for visual accessibility design in virtual reality, with a focus on reading. This is coupled with a hands-on study of eight reading applications in virtual reality to evaluate how accessibility design is currently implemented in existing products. Finally, we present a framework that integrates the design principles resulting from our analysis and study, and implement a proof-of-concept for this framework using browser-based graphics (Figure 4 and 5) to demonstrate the feasibility of our proposal with modern virtual reality technology.

Figure 4. Application prototype: The global overview of the newspaper page is shown side-by-side with the enlarged text and images of the highlighted region. Navigation hints above the card show what type of content is displayed (e.g. photo, heading, paragraph) and whether the card can be selected (i.e. highlighted in light blue) to reveal further content. Text and images of the newspaper are purely for demonstrating a proof-of-concept. Excerpted from 7 May 2019 issue of ©Le Monde.
Figure 5. The accessibility menu provides a number of functions including (1) showing/hiding the page and menu view to personalize the view space, (2) invert foreground and background color only for text content, and (3) change the print size. Text on the cards excerpted from 7 May 2019 issue of ©Le Monde

This work is presented in [26].