Recognizing Freeform Digital Ink Annotations

  • Michael Shilman
  • Zile Wei
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3163)

Abstract

Annotations on digital documents have clear advantages over annotations on paper. They can be archived, shared, searched, and easily manipulated. Freeform digital ink annotations add the flexibility and natural expressiveness of pen and paper, but sacrifice some of the structure inherent to annotations created with mouse and keyboard. For instance, current ink annotation systems do not anchor the ink so that it can be logically reflowed as the document is resized or edited. If digital ink annotations do not reflow to keep up with the portions of the document they are annotating, the ink can become meaningless or even misleading. In this paper, we describe an approach to recognizing digital ink annotations to infer this structure, restoring the strengths of more structured digital annotations to a preferable freeform medium. Our solution is easily extensible to support new annotation types and allows us to efficiently resolve ambiguities between different annotation elements in real-time.

Keywords

Context Feature Context Word Annotation Type Vertical Range Digital Document 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Michael Shilman
    • 1
  • Zile Wei
    • 2
  1. 1.Microsoft ResearchRedmondUSA
  2. 2.EECS DepartmentUC BerkeleyBerkeleyUSA

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