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dc.contributor.authorIsola, Phillip John
dc.contributor.authorXiao, Jianxiong
dc.contributor.authorParikh, Devi
dc.contributor.authorTorralba, Antonio
dc.contributor.authorOliva, Aude
dc.date.accessioned2014-10-20T14:29:09Z
dc.date.available2014-10-20T14:29:09Z
dc.date.issued2014-06
dc.date.submitted2013-05
dc.identifier.issn0162-8828
dc.identifier.issn2160-9292
dc.identifier.urihttp://hdl.handle.net/1721.1/90984
dc.description.abstractWhen glancing at a magazine, or browsing the Internet, we are continuously exposed to photographs. Despite this overflow of visual information, humans are extremely good at remembering thousands of pictures along with some of their visual details. But not all images are equal in memory. Some stick in our minds while others are quickly forgotten. In this paper, we focus on the problem of predicting how memorable an image will be. We show that memorability is an intrinsic and stable property of an image that is shared across different viewers, and remains stable across delays. We introduce a database for which we have measured the probability that each picture will be recognized after a single view. We analyze a collection of image features, labels, and attributes that contribute to making an image memorable, and we train a predictor based on global image descriptors. We find that predicting image memorability is a task that can be addressed with current computer vision techniques. While making memorable images is a challenging task in visualization, photography, and education, this work is a first attempt to quantify this useful property of images.en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (Grant 1016862)en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (CAREER Award 0747120)en_US
dc.description.sponsorshipUnited States. Intelligence Advanced Research Projects Activity (Department of the Interior Contract D10PC20023)en_US
dc.description.sponsorshipUnited States. Office of Naval Research. Multidisciplinary University Research Initiative (N000141010933)en_US
dc.description.sponsorshipGoogle (Firm)en_US
dc.description.sponsorshipXerox (Firm)en_US
dc.description.sponsorshipNational Science Foundation (U.S.). Graduate Research Fellowshipen_US
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/TPAMI.2013.200en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceMIT web domainen_US
dc.titleWhat Makes a Photograph Memorable?en_US
dc.typeArticleen_US
dc.identifier.citationIsola, Phillip, Jianxiong Xiao, Devi Parikh, Antonio Torralba, and Aude Oliva. “What Makes a Photograph Memorable?” IEEE Trans. Pattern Anal. Mach. Intell. 36, no. 7 (July 2014): 1469–1482.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciencesen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.mitauthorIsola, Phillip Johnen_US
dc.contributor.mitauthorXiao, Jianxiongen_US
dc.contributor.mitauthorTorralba, Antonioen_US
dc.contributor.mitauthorOliva, Audeen_US
dc.relation.journalIEEE Transactions on Pattern Analysis and Machine Intelligenceen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsIsola, Phillip; Xiao, Jianxiong; Parikh, Devi; Torralba, Antonio; Oliva, Audeen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-1411-6704
dc.identifier.orcidhttps://orcid.org/0000-0003-4915-0256
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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