Computational Aesthetics 2008: Automatically mimicking unique hand-drawn pencil lines

  • Authors:
  • Zainab AlMeraj;Brian Wyvill;Tobias Isenberg;Amy A. Gooch;Richard Guy

  • Affiliations:
  • David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada N2L 3G1 and University of Victoria, Canada and Kuwait University, Kuwait;University of Victoria, Canada;University of Groningen, The Netherlands;University of Victoria, Canada;University of Calgary, Canada

  • Venue:
  • Computers and Graphics
  • Year:
  • 2009

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Abstract

In applications such as architecture, early design sketches containing accurate line drawings often mislead the target audience. Approximate human-drawn sketches are typically accepted as a better way of demonstrating fundamental design concepts. To this end we have designed an algorithm that creates lines that perceptually resemble human-drawn lines. Our algorithm works directly with input point data and a physically based mathematical model of human arm movement. Our algorithm generates unique lines of arbitrary length given the end points of a line, without relying on a database of human-drawn lines. We found that an observational analysis obtained through various user studies of human lines made a bigger impact on the algorithm than a statistical analysis. Additional studies have shown that the algorithm produces lines that are perceptually indistinguishable from that of a hand-drawn straight pencil line. A further expansion to the system resulted in mimicked dashed lines.