Building a Gold Standard for Perceptual Sketch Similarity

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dc.contributor.authorCakmak, S.en_US
dc.contributor.authorSezgin, T. M.en_US
dc.contributor.editorErgun Akleman, Lyn Bartram, Anıl Çamcı, Angus Forbes, Penousal Machadoen_US
dc.date.accessioned2016-07-18T16:42:36Z
dc.date.available2016-07-18T16:42:36Z
dc.date.issued2016
dc.description.abstractSimilarity is among the most basic concepts studied in psychology. Yet, there is no unique way of assessing similarity of two objects. In the sketch recognition domain, many tasks such as classification, detection or clustering require measuring the level of similarity between sketches. In this paper, we propose a carefully designed experiment setup to construct a gold standard for measuring the similarity of sketches. Our setup is based on table scaling, and allows efficient construction of a measure of similarity for large datasets containing hundreds of sketches in reasonable time scales. We report the results of an experiment involving a total of 9 unique assessors, and 8 groups of sketches, each containing 300 drawings. The results show high interrater agreement between the assessors, which makes the constructed gold standard trustworthy.en_US
dc.description.sectionheadersPosters
dc.description.seriesinformationExpressive 2016 - Posters, Artworks, and Bridging Papers
dc.identifier.doi10.2312/exp.20161256
dc.identifier.isbn978-3-03868-021-5
dc.identifier.pages5-6
dc.identifier.urihttps://doi.org/10.2312/exp.20161256
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/exp20161256
dc.publisherThe Eurographics Associationen_US
dc.subjectH.5.2 [User Interfaces]
dc.subjectEvaluation/methodology
dc.subjectInteraction styles (e.g.
dc.subjectcommands
dc.subjectmenus
dc.subjectforms
dc.subjectdirect manipulation) H.1.2 [User/Machine Systems]
dc.subjectHuman factors
dc.subjectHuman information processing
dc.titleBuilding a Gold Standard for Perceptual Sketch Similarityen_US
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Expressive 2016 - Posters, Artworks, and Bridging Papers