How to make a Quick$: Using Hierarchical Clustering toImprove the Efficiency of the Dollar Recognizer
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We present Quick$ (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.
BibTeX
@inproceedings {SBM:SBM11:103-108,
booktitle = {Eurographics Workshop on Sketch-Based Interfaces and Modeling},
editor = {Tracy Hammond and Andy Nealen},
title = {{How to make a Quick$: Using Hierarchical Clustering toImprove the Efficiency of the Dollar Recognizer}},
author = {Reaver, J. and Stahovich, T. F. and Herold, J.},
year = {2011},
publisher = {The Eurographics Association},
ISSN = {1812-3503},
ISBN = {978-1-4503-0906-6},
DOI = {10.2312/SBM/SBM11/103-108}
}
booktitle = {Eurographics Workshop on Sketch-Based Interfaces and Modeling},
editor = {Tracy Hammond and Andy Nealen},
title = {{How to make a Quick$: Using Hierarchical Clustering toImprove the Efficiency of the Dollar Recognizer}},
author = {Reaver, J. and Stahovich, T. F. and Herold, J.},
year = {2011},
publisher = {The Eurographics Association},
ISSN = {1812-3503},
ISBN = {978-1-4503-0906-6},
DOI = {10.2312/SBM/SBM11/103-108}
}