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dc.contributor.authorKhosla, Aditya
dc.contributor.authorBainbridge, Wilma A.
dc.contributor.authorTorralba, Antonio
dc.contributor.authorOliva, Aude
dc.date.accessioned2014-10-20T14:45:18Z
dc.date.available2014-10-20T14:45:18Z
dc.date.issued2013-12
dc.identifier.isbn978-1-4799-2840-8
dc.identifier.issn1550-5499
dc.identifier.urihttp://hdl.handle.net/1721.1/90986
dc.description.abstractContemporary life bombards us with many new images of faces every day, which poses non-trivial constraints on human memory. The vast majority of face photographs are intended to be remembered, either because of personal relevance, commercial interests or because the pictures were deliberately designed to be memorable. Can we make a portrait more memorable or more forgettable automatically? Here, we provide a method to modify the memorability of individual face photographs, while keeping the identity and other facial traits (e.g. age, attractiveness, and emotional magnitude) of the individual fixed. We show that face photographs manipulated to be more memorable (or more forgettable) are indeed more often remembered (or forgotten) in a crowd-sourcing experiment with an accuracy of 74%. Quantifying and modifying the 'memorability' of a face lends itself to many useful applications in computer vision and graphics, such as mnemonic aids for learning, photo editing applications for social networks and tools for designing memorable advertisements.en_US
dc.description.sponsorshipXerox (Firm) (Research Award)en_US
dc.description.sponsorshipGoogle (Firm) (Research Award)en_US
dc.description.sponsorshipUnited States. Office of Naval Research. Multidisciplinary University Research Initiative (N000141010933)en_US
dc.description.sponsorshipAmerican Society for Engineering Education. National Defense Science and Engineering Graduate Fellowshipen_US
dc.description.sponsorshipFacebook (Firm) (Fellowship)en_US
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/ICCV.2013.397en_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.titleModifying the Memorability of Face Photographsen_US
dc.typeArticleen_US
dc.identifier.citationKhosla, Aditya, Wilma A. Bainbridge, Antonio Torralba, and Aude Oliva. “Modifying the Memorability of Face Photographs.” 2013 IEEE International Conference on Computer Vision (December 2013).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.mitauthorKhosla, Adityaen_US
dc.contributor.mitauthorBainbridge, Wilma A.en_US
dc.contributor.mitauthorTorralba, Antonioen_US
dc.contributor.mitauthorOliva, Audeen_US
dc.relation.journalProceedings of the 2013 IEEE International Conference on Computer Visionen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dspace.orderedauthorsKhosla, Aditya; Bainbridge, Wilma A.; Torralba, Antonio; Oliva, Audeen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-0007-3352
dc.identifier.orcidhttps://orcid.org/0000-0003-4915-0256
mit.licenseOPEN_ACCESS_POLICYen_US


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