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dc.contributor.authorZhen, Jacky (Shunjie)en_US
dc.contributor.authorBlagojevic, Rachelen_US
dc.contributor.authorPlimmer, Berylen_US
dc.contributor.editorKaran Singh and Levent Burak Karaen_US
dc.date.accessioned2014-01-28T18:19:35Z
dc.date.available2014-01-28T18:19:35Z
dc.date.issued2012en_US
dc.identifier.isbn978-3-905674-42-2en_US
dc.identifier.issn1812-3503en_US
dc.identifier.urihttp://dx.doi.org/10.2312/SBM/SBM12/067-075en_US
dc.description.abstractLabeled ink stroke data is essential to the development and evaluation of sketch recognizers. Manually labeling strokes is a tedious, time-consuming, and error prone task; and very few tools are available to facilitate this. We propose a new and intuitive method of automatic labeling for single stroke primitives. This involves building a recognizer from a partially labeled dataset. This recognizer is then used to identify and automatically label the remaining data, therefore reducing the amount of manual labeling required by researchers. An evaluation comparing manual labeling against our new auto labeling method shows that users are able to label significantly faster and produce less errors using auto labeling. Furthermore, users found auto labeling easier and more preferable.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.7.5 [Document and Text Processing]: Document Capture: Graphics recognition and interpretation, I.2.5 [Artificial Intelligence]: Programming Languages and Software: Expert system tools and techniques.en_US
dc.titleAutomated Labeling of Ink Stroke Dataen_US
dc.description.seriesinformationEurographics Workshop on Sketch-Based Interfaces and Modelingen_US


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