Tools for the Efficient Generation of Hand-Drawn Corpora Based on Context-Free Grammars

dc.contributor.authorMacLean, Scotten_US
dc.contributor.authorTausky, Daviden_US
dc.contributor.authorLabahn, Georgeen_US
dc.contributor.authorLank, Edwarden_US
dc.contributor.authorMarzouk, Miretteen_US
dc.contributor.editorCindy Grimm and Joseph J. LaViola, Jr.en_US
dc.date.accessioned2014-01-28T18:04:21Z
dc.date.available2014-01-28T18:04:21Z
dc.date.issued2009en_US
dc.description.abstractIn sketch recognition systems, ground-truth data sets serve to both train and test recognition algorithms. Unfortunately, generating data sets that are sufficiently large and varied is frequently a costly and time-consuming endeavour. In this paper, we present a novel technique for creating a large and varied ground-truthed corpus for hand drawn math recognition. Candidate math expressions for the corpus are generated via random walks through a context-free grammar, the expressions are transcribed by human writers, and an algorithm automatically generates ground-truth data for individual symbols and inter-symbol relationships within the math expressions. While the techniques we develop in this paper are illustrated through the creation of a ground-truthed corpus of mathematical expressions, they are applicable to any sketching domain that can be described by a formal grammar.en_US
dc.description.seriesinformationEUROGRAPHICS Workshop on Sketch-Based Interfaces and Modelingen_US
dc.identifier.isbn978-3-905674-19-4en_US
dc.identifier.issn1812-3503en_US
dc.identifier.urihttps://doi.org/10.2312/SBM/SBM09/125-132en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.5.5 [Computing Methodologies]: Pattern Recognition-Implementationen_US
dc.titleTools for the Efficient Generation of Hand-Drawn Corpora Based on Context-Free Grammarsen_US
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