Online Composite Sketchy Shape Recognition Based on Bayesian Networks

  • Zhengxing Sun
  • Lisha Zhang
  • Bin Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4222)


This paper presents a novel approach for online multi-strokes composite sketchy shape recognition based on Bayesian Networks. By means of the definition of a double-level Bayesian networks, a classifier is designed to model the intrinsic temporal orders among the strokes effectively, where a sketchy shape is modeled with the relationships not only between a stroke and its neighbouring strokes, but also between a stroke and all of its subsequence.. The drawing-style tree is then adopted to capture the users’ accustomed drawing styles and simplify the training and recognition of Bayesian network classifier. The experiments prove both effectiveness and efficiency of the proposed method.


Support Vector Machine Feature Vector Bayesian Network Support Vector Machine Classifier Shape Class 
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 2006

Authors and Affiliations

  • Zhengxing Sun
    • 1
  • Lisha Zhang
    • 1
  • Bin Zhang
    • 1
  1. 1.State Key Lab for Novel Software TechnologyNanjing UniversityPR China

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