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dc.contributor.authorWang, Xi
dc.contributor.authorBylinskii, Zoya
dc.contributor.authorHertzmann, Aaron
dc.contributor.authorPepperell, Robert
dc.date.accessioned2021-04-22T15:51:48Z
dc.date.available2021-04-22T15:51:48Z
dc.date.issued2020-11-01
dc.identifier.citationWang, X., Bylinskii, Z., Hertzmann, A. and Pepperell, R. (2020) 'Toward Quantifying Ambiguities in Artistic Images', ACM Transactions on Applied Perception (TAP), 17(4), pp.1-10. https://doi.org/10.1145/3418054en_US
dc.identifier.urihttp://hdl.handle.net/10369/11368
dc.descriptionArticle published in ACM Transactions on Applied Perception available at https://doi.org/10.1145/3418054en_US
dc.description.abstractIt has long been hypothesized that perceptual ambiguities play an important role in aesthetic experience: A work with some ambiguity engages a viewer more than one that does not. However, current frameworks for testing this theory are limited by the availability of stimuli and data collection methods. This article presents an approach to measuring the perceptual ambiguity of a collection of images. Crowdworkers are asked to describe image content, after different viewing durations. Experiments are performed using images created with Generative Adversarial Networks, using the Artbreeder website. We show that text processing of viewer responses can provide a fine-grained way to measure and describe image ambiguities.en_US
dc.language.isoenen_US
dc.publisherACMen_US
dc.relation.ispartofseriesACM Transactions on Applied Perception;
dc.titleToward quantifying ambiguities in artistic imagesen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1145/3418054
dcterms.dateAccepted2020-11
rioxxterms.versionAMen_US


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    Fovolab aspires to push the boundaries of understanding perceptual experience – how we perceive and are aware of the world.

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