How to make a Quick$: Using Hierarchical Clustering toImprove the Efficiency of the Dollar Recognizer

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dc.contributor.authorReaver, J.en_US
dc.contributor.authorStahovich, T. F.en_US
dc.contributor.authorHerold, J.en_US
dc.contributor.editorTracy Hammond and Andy Nealenen_US
dc.date.accessioned2013-10-31T10:24:23Z
dc.date.available2013-10-31T10:24:23Z
dc.date.issued2011en_US
dc.description.abstractWe 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.en_US
dc.description.seriesinformationEurographics Workshop on Sketch-Based Interfaces and Modelingen_US
dc.identifier.isbn978-1-4503-0906-6en_US
dc.identifier.issn1812-3503en_US
dc.identifier.urihttps://doi.org/10.2312/SBM/SBM11/103-108en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.7.5 [Computer Graphics]: Document Capture Graphics recognition and interpretationen_US
dc.titleHow to make a Quick$: Using Hierarchical Clustering toImprove the Efficiency of the Dollar Recognizeren_US
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SBM11: Sketch Based Interfaces and Modeling 2011