| dc.contributor.author | Yuen, Jenny | |
| dc.contributor.author | Russell, Bryan | |
| dc.contributor.author | Liu, Ce | |
| dc.contributor.author | Torralba, Antonio | |
| dc.date.accessioned | 2011-05-11T18:20:17Z | |
| dc.date.available | 2011-05-11T18:20:17Z | |
| dc.date.issued | 2009-09 | |
| dc.identifier.isbn | 978-1-4244-4420-5 | |
| dc.identifier.issn | 1550-5499 | |
| dc.identifier.other | INSPEC Accession Number: 11367750 | |
| dc.identifier.uri | http://hdl.handle.net/1721.1/62816 | |
| dc.description.abstract | Currently, video analysis algorithms suffer from lack of information regarding the objects present, their interactions, as well as from missing comprehensive annotated video databases for benchmarking. We designed an online and openly accessible video annotation system that allows anyone with a browser and internet access to efficiently annotate object category, shape, motion, and activity information in real-world videos. The annotations are also complemented with knowledge from static image databases to infer occlusion and depth information. Using this system, we have built a scalable video database composed of diverse video samples and paired with human-guided annotations. We complement this paper demonstrating potential uses of this database by studying motion statistics as well as cause-effect motion relationships between objects. | en_US |
| dc.description.sponsorship | National Science Foundation (U.S.) (CAREER award IIS 0747120) | en_US |
| dc.description.sponsorship | National Defense Science and Engineering Graduate Fellowship | en_US |
| dc.language.iso | en_US | |
| dc.publisher | Institute of Electrical and Electronics Engineers | en_US |
| dc.relation.isversionof | http://dx.doi.org/10.1109/ICCV.2009.5459289 | en_US |
| dc.rights | Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. | en_US |
| dc.source | MIT web domain | en_US |
| dc.title | LabelMe video: Building a video database with human annotations | en_US |
| dc.type | Article | en_US |
| dc.identifier.citation | Yuen, J. et al. “LabelMe Video: Building a Video Database with Human Annotations.” Computer Vision, 2009 IEEE 12th International Conference On. 2009. 1451-1458. Copyright © 2009, IEEE | 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.approver | Torralba, Antonio | |
| dc.contributor.mitauthor | Yuen, Jenny | |
| dc.contributor.mitauthor | Liu, Ce | |
| dc.contributor.mitauthor | Torralba, Antonio | |
| dc.relation.journal | IEEE International Conference on Computer Vision. (12th, 2009) | en_US |
| dc.eprint.version | Final published version | en_US |
| dc.type.uri | http://purl.org/eprint/type/ConferencePaper | en_US |
| dspace.orderedauthors | Yuen, Jenny; Russell, Bryan; Ce Liu, Bryan; Torralba, Antonio | en |
| dc.identifier.orcid | https://orcid.org/0000-0003-4915-0256 | |
| mit.license | PUBLISHER_POLICY | en_US |
| mit.metadata.status | Complete | |
