Please note: This PhD seminar will take place in DC 1304 and virtually over Zoom.
Damien Masson, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Daniel Vogel
Extracting underlying data from rasterized charts is tedious and inaccurate; values might be partially occluded or hard to distinguish, and the quality of the image limits the precision of the data being recovered. To address these issues, we introduce a semi-automatic system leveraging vector charts to extract the underlying data easily and accurately. The system is designed to make the most of vector information by relying on a drag-and-drop interface combined with selection, filtering, and previsualization features.
A user study showed that participants spent less than 4 minutes to accurately recover data from charts published at CHI with diverse styles, thousands of data points, a combination of different encodings, and elements partially or completely occluded. Compared to other approaches relying on raster images, our tool successfully recovered all data, even when hidden, with a 78% lower relative error.
To attend this seminar in person, please go to DC 1304. You can also attend virtually using Zoom at https://uwaterloo.zoom.us/j/98631705869.
200 University Avenue West
Waterloo, ON N2L 3G1