SAR: Stroke Authorship Recognition

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dc.contributor.authorShaheen, Saraen_US
dc.contributor.authorRockwood, Alynen_US
dc.contributor.authorGhanem, Bernarden_US
dc.contributor.editorChen, Min and Zhang, Hao (Richard)en_US
dc.date.accessioned2016-09-27T10:02:03Z
dc.date.available2016-09-27T10:02:03Z
dc.date.issued2016
dc.description.abstractAre simple strokes unique to the artist or designer who renders them? If so, can this idea be used to identify authorship or to classify artistic drawings? Also, could training methods be devised to develop particular styles? To answer these questions, we propose the Stroke Authorship Recognition (SAR) approach, a novel method that distinguishes the authorship of 2D digitized drawings. SAR converts a drawing into a histogram of stroke attributes that is discriminative of authorship. We provide extensive classification experiments on a large variety of data sets, which validate SAR's ability to distinguish unique authorship of artists and designers. We also demonstrate the usefulness of SAR in several applications including the detection of fraudulent sketches, the training and monitoring of artists in learning a particular new style and the first quantitative way to measure the quality of automatic sketch synthesis tools.Are simple strokes unique to the artist or designer who renders them? If so, can this idea be used to identify authorship or to classify artistic drawings? Also, could training methods be devised to develop particular styles? To answer these questions, we propose the Stroke Authorship Recognition (SAR) approach, a novel method that distinguishes the authorship of 2D digitized drawings. SAR converts a drawing into a histogram of stroke attributes that is discriminative of authorship.en_US
dc.description.number6
dc.description.sectionheadersArticles
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume35
dc.identifier.doi10.1111/cgf.12733
dc.identifier.issn1467-8659
dc.identifier.pages73-86
dc.identifier.urihttps://doi.org/10.1111/cgf.12733
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf12733
dc.publisherCopyright © 2016 The Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectsketch
dc.subjectstroke
dc.subjectstroke segments
dc.subjectstyle
dc.subjectauthorship recognition
dc.subjectfraud detection
dc.subjectsketch training
dc.subjectCategories and Subject Descriptors: image processing, computer vision — shape recognition
dc.titleSAR: Stroke Authorship Recognitionen_US
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