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ReVision : Automated Classification, Analysis and Redesign of Chart Images

ReVision : Automated Classification, Analysis and Redesign of Chart Images. Paper by: Manolis Savva , Nicholas Kong, Arti Chhajta , Li Fei-Fei , Maneesh Agrawala , and Jeffrey Heer Presentation by: Christopher MacLellan. Charts are an important tool for conveying quantitative information.

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ReVision : Automated Classification, Analysis and Redesign of Chart Images

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  1. ReVision: Automated Classification, Analysis and Redesign of Chart Images Paper by: ManolisSavva, Nicholas Kong, ArtiChhajta, Li Fei-Fei, ManeeshAgrawala, and Jeffrey Heer Presentation by: Christopher MacLellan

  2. Charts are an important tool for conveying quantitative information

  3. But sometimes they are poorly designed…

  4. Imagine a tool that could automatically redesign charts.

  5. ReVision is a tool that automates chart redesign in 3 steps.

  6. Step 1: Classification Performed For all images Performed Once for All images Performed For all images

  7. The resulting classification is better than previous approaches

  8. Step 2: Mark and Data Extraction • Looked at two kinds of charts: bar charts and pie charts. • Made the following simplifying assumptions: • Charts contain 2D marks and do not contain 3D effects. • Each mark is solidly shaded using a single color. Marks are not shaded using textures or steep gradients. • Marks encode a data tuple, where at least one dimension is quantitative and one dimension is nominal. For example, in a bar chart the height of a bar represents a quantitative value, while a nominal label often appears below the bar. • Bar charts do not contain stacked bars. • Bar chart axes appear at the left and bottom of the chart.

  9. Getting marks and data from bar charts Extract Rectangles Get orientation and base axis Extract data

  10. Getting marks and data from pie charts Fit Ellipse Sample points inside ellipse, unroll, and extract proportions

  11. Able to extract data from 79% of bar charts and 62% of pie charts

  12. Step 3: Redesign

  13. Discussion Points • Is this system practical for real world use? Is it really better than manually interpreting the data from a chart, entering it into a system, and getting a new gallery of redesigned charts? Especially considering that the extraction of text-level features currently requires humans (although they argue the crowd could be used). • In Licklider's man-computer symbiosis paper he talks a lot about how computers should graph, graph, and re-graph things. How does this work fit into that paradigm? Could this system be viewed as symbiotic with a human user? Or does it also need to be able to analyze the data in more complex ways? • Can you think of some situations where you would like to see this technology used?

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