Reading #13: Ink Features for Diagram Recognition

by Rachel Patel, Beryl Plimmer, John Grundy, and Ross Ihaka

Comments: Jianjie

This paper aims to perform more accurate diagram recognition by performing a statistical analysis of features used for recognizing various diagram components from sketched samples. This is pretty much an introduction to some of the important concepts in sketch recognition and illustrates some general approaches to sketch recognition. The paper particularly focuses on shape vs. text.

The authors took 46 features grouped into 7 categories. They collected some sketches from 26 participants which contained some diagram elements and text. They used a statistical partitioning technique to find which features can best split the strokes into shape or text strokes and then constructed decision trees with significant features toward the start of the tree.

They tested their methods with some existing shape v text systems and found some interesting results...

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Sketch recognition still remains in its infancy despite its age, and formal analyses like this are important to help us understand the processes and achieve greater recognition performance. This work seems kind of inconclusive, however, and I didn't understand the results very well.