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Interpreting Sloppy Stick Figures by Graph Rectification and Constraint-Based Matching

  • James V. Mahoney
  • Markus P. J. Fromherz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2390)

Abstract

Programs for understanding hand-drawn sketches and diagrams must interpret curvilinear configurations that are sloppily drawn and highly variable in form. We propose a two-stage subgraph matching framework for sketch recognition that can accommodate great variability in form and yet provide efficient matching and easy extensibility to new configurations. First, a rectification stage corrects the initial data graph for the common deviations of each kind of constituent local configuration from its ideal form. The model graph is then matched directly to the data by a constraint-based subgraph matching process, without the need for complex error-tolerance. We explore the approach in the domain of human stick figures in diverse poses.

Keywords

Minimum Span Tree Constraint Satisfaction Problem Data Graph Mutual Exclusion Curve Segment 
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 2002

Authors and Affiliations

  • James V. Mahoney
    • 1
  • Markus P. J. Fromherz
    • 1
  1. 1.Xerox Palo Alto Research CenterPalo Alto

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