How to make a Quick$: using hierarchical clustering to improve the efficiency of the Dollar Recognizer

Authors:
J. Reaver;T. F. Stahovich;J. Herold
Affiliations:
University of California, Riverside, CA;University of California, Riverside, CA;University of California, Riverside, CA
Venue:
Proceedings of the Eighth Eurographics Symposium on Sketch-Based Interfaces and Modeling
Year:
2011

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Abstract

We present Quick$ (QuickBuck), an extension to the Dollar Recognizer designed to improve recognition efficiency. While the Dollar Recognizer must search all training templates to recognize an unknown symbol, Quick$ employs hierarchical clustering along with branch and bound search to do this more efficiently. Experiments have demonstrated that Quick$ is almost always faster than the Dollar Recognizer and always selects the same best-match templates.