| dc.contributor.author | Zhou, Bolei | |
| dc.contributor.author | Liu, Liu | |
| dc.contributor.author | Oliva, Aude | |
| dc.contributor.author | Torralba, Antonio | |
| dc.date.accessioned | 2014-10-20T18:03:08Z | |
| dc.date.available | 2014-10-20T18:03:08Z | |
| dc.date.issued | 2014 | |
| dc.identifier.isbn | 978-3-319-10577-2 | |
| dc.identifier.isbn | 978-3-319-10578-9 | |
| dc.identifier.issn | 0302-9743 | |
| dc.identifier.issn | 1611-3349 | |
| dc.identifier.uri | http://hdl.handle.net/1721.1/90999 | |
| dc.description.abstract | After hundreds of years of human settlement, each city has formed a distinct identity, distinguishing itself from other cities. In this work, we propose to characterize the identity of a city via an attribute analysis of 2 million geo-tagged images from 21 cities over 3 continents. First, we estimate the scene attributes of these images and use this representation to build a higher-level set of 7 city attributes, tailored to the form and function of cities. Then, we conduct the city identity recognition experiments on the geo-tagged images and identify images with salient city identity on each city attribute. Based on the misclassification rate of the city identity recognition, we analyze the visual similarity among different cities. Finally, we discuss the potential application of computer vision to urban planning. | en_US |
| dc.description.sponsorship | National Science Foundation (U.S.) (Grant 1016862) | en_US |
| dc.description.sponsorship | Google (Firm) (Research Award) | en_US |
| dc.language.iso | en_US | |
| dc.publisher | Springer-Verlag | en_US |
| dc.relation.isversionof | http://dx.doi.org/10.1007/978-3-319-10578-9_34 | en_US |
| dc.rights | Creative Commons Attribution-Noncommercial-Share Alike | en_US |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | en_US |
| dc.source | MIT web domain | en_US |
| dc.title | Recognizing City Identity via Attribute Analysis of Geo-tagged Images | en_US |
| dc.type | Article | en_US |
| dc.identifier.citation | Zhou, Bolei, Liu Liu, Aude Oliva, and Antonio Torralba. “Recognizing City Identity via Attribute Analysis of Geo-Tagged Images.” Lecture Notes in Computer Science (2014): 519–534. | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Urban Studies and Planning | en_US |
| dc.contributor.mitauthor | Zhou, Bolei | en_US |
| dc.contributor.mitauthor | Liu, Liu | en_US |
| dc.contributor.mitauthor | Oliva, Aude | en_US |
| dc.contributor.mitauthor | Torralba, Antonio | en_US |
| dc.relation.journal | Computer Vision – ECCV 2014 | en_US |
| dc.eprint.version | Author's final manuscript | en_US |
| dc.type.uri | http://purl.org/eprint/type/ConferencePaper | en_US |
| eprint.status | http://purl.org/eprint/status/NonPeerReviewed | en_US |
| dspace.orderedauthors | Zhou, Bolei; Liu, Liu; Oliva, Aude; Torralba, Antonio | en_US |
| dc.identifier.orcid | https://orcid.org/0000-0002-3570-4396 | |
| dc.identifier.orcid | https://orcid.org/0000-0003-4915-0256 | |
| mit.license | OPEN_ACCESS_POLICY | en_US |
| mit.metadata.status | Complete | |
