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Textension: Digitally Augmenting Document Spaces in Analog Texts


Adam James Bradley, Christopher Collins, Victor Sawal, and Sheelagh Carpendale

In this paper, we present a framework that allows people who work with analog texts to leverage the affordances of digital technology, such as data visualization, computational linguistics, and search, using any web-based mobile device with a camera. After taking a picture of a particular page or set of pages from a text or uploading an existing image, our prototype system builds an interactive digital object that automatically inserts visualizations and interactive elements into the document. Leveraging the findings of previous studies, our framework augments the reading of analog texts with digital tools, making it possible to work with texts in both a digital and analog environment.

Check out our online demo.


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This work was supported by NSERC Canada Research Chairs, The Canada Foundation for Innovation – Cyberinfrastructure Fund, and the Province of Ontario – Ontario Research Fund.



Eye Tracking for Target Acquisition in Sparse Visualizations

In this paper, we present a novel marker-free method for identifying screens of interest when using head-mounted eye-tracking for visualization in cluttered and multi-screen environments. We offer a solution to discerning visualization entities from sparse backgrounds by incorporating edge-detection into the existing pipeline. Our system allows for both more efficient screen identification and improved accuracy over the state-of-the-art ORB algorithm.

The source code for this project is available on our Github.



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