Specifying label layout style by example

ABSTRACT

Creating high-quality label layouts in a particular visual style is a time-consuming process. Although automated labeling algorithms can aid the layout process, expert design knowledge is required to tune these algorithms so that they produce layouts which meet the designer's expectations. We propose a system which can learn a labellayout style from a single example layout and then apply this style to new labeling problems. Because designers find it much easier to create example layouts than tune algorithmic parameters, our system provides a more natural workflow for graphic designers. We demonstrate that our system is capable of learning a variety of label layout styles from examples.

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Index Terms

• Computing methodologies

  • Computer graphics

  • Machine learning

    • Learning paradigms

    • Machine learning approaches

      • Markov decision processes

• Human-centered computing

  • Human computer interaction (HCI)

• Theory of computation

  • Theory and algorithms for application domains

    • Machine learning theory

      • Markov decision processes