The representation and use of a visual lexicon for automated graphics generation

  • Authors:
  • Michelle X. Zhou;Steven K. Feiner

  • Affiliations:
  • Dept. of Computer Science, Columbia University, New York, NY;Dept. of Computer Science, Columbia University, New York, NY

  • Venue:
  • IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
  • Year:
  • 1997

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Abstract

Most automated graphics generation systems employ either a constructive or a parametric graphics synthesis approach. Constructive graphics synthesis is a deductive approach that builds visual presentations from scratch by gluing together the most basic visual variables. Conversely, parametric graphics synthesis defines a set of parametrized visual models and interprets the information to be presented through instantiation of the selected model. To increase efficiency, we have combined parametric and constructive approaches in a system called IMPROVISE. In this paper, we focus on the parametric aspect of our approach. We present a comprehensive, general, and extensible formalism to represent a visual lexicon for use in automated graphics generation. A visual lexicon is a collection of parametrized primitive visual objects that serve as building blocks for constructing more complex visual presentations. We also illustrate how this representation can be effectively employed to aid the selection and instantiation of a visual lexical item in the graphics generation process. Examples are given from IMPROVISE to demonstrate the representation and use of this visual lexicon.