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CHI2023顶会

ChartDetective: Easy and Accurate Interactive Data Extraction from Complex Vector Charts

Damien Masson, Sylvain Malacria, Daniel Vogel, Edward Lank, Géry Casiez

2023年份
22被引次数
11顶会引用

摘要

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.

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