Show simple item record

dc.contributor.authorMobahi, Hossein
dc.contributor.authorLiu, Ce
dc.contributor.authorFreeman, William T.
dc.date.accessioned2015-12-16T23:32:56Z
dc.date.available2015-12-16T23:32:56Z
dc.date.issued2014-06
dc.identifier.isbn978-1-4799-5118-5
dc.identifier.urihttp://hdl.handle.net/1721.1/100401
dc.description.abstractLearning a low-dimensional representation of images is useful for various applications in graphics and computer vision. Existing solutions either require manually specified landmarks for corresponding points in the images, or are restricted to specific objects or shape deformations. This paper alleviates these limitations by imposing a specific model for generating images, the nested composition of color, shape, and appearance. We show that each component can be approximated by a low-dimensional subspace when the others are factored out. Our formulation allows for efficient learning and experiments show encouraging results.en_US
dc.description.sponsorshipShell Researchen_US
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/CVPR.2014.172en_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.titleA Compositional Model for Low-Dimensional Image Set Representationen_US
dc.typeArticleen_US
dc.identifier.citationMobahi, Hossein, Ce Liu, and William T. Freeman. “A Compositional Model for Low-Dimensional Image Set Representation.” 2014 IEEE Conference on Computer Vision and Pattern Recognition (June 2014).en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.mitauthorMobahi, Hosseinen_US
dc.contributor.mitauthorFreeman, William T.en_US
dc.relation.journalProceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognitionen_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.orderedauthorsMobahi, Hossein; Liu, Ce; Freeman, William T.en_US
dc.identifier.orcidhttps://orcid.org/0000-0001-8074-1092
dc.identifier.orcidhttps://orcid.org/0000-0002-2231-7995
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record