KAUST DepartmentComputer Science Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
Office of the VP
Visual Computing Center (VCC)
Online Publication Date2015-10-15
Print Publication Date2016-09
Permanent link to this recordhttp://hdl.handle.net/10754/621413
MetadataShow full item record
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. © 2015 The Eurographics Association and John Wiley & Sons Ltd.
CitationShaheen S, Rockwood A, Ghanem B (2015) SAR: Stroke Authorship Recognition. Computer Graphics Forum 35: 73–86. Available: http://dx.doi.org/10.1111/cgf.12733.
SponsorsKing Abdullah University of Science and Technology
JournalComputer Graphics Forum