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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yuen, J. Russell, B. Ce Liu Torralba, A. |
| Copyright Year | 2009 |
| Description | Author affiliation: MIT, USA (Yuen, J.; Ce Liu; Torralba, A.) || INRIA / Ecole Normale Supérieure, France (Russell, B.) |
| 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. |
| Starting Page | 1451 |
| Ending Page | 1458 |
| File Size | 4094074 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781424444205 |
| ISSN | 15505499 |
| DOI | 10.1109/ICCV.2009.5459289 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-09-29 |
| Publisher Place | Japan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Humans Image databases Algorithm design and analysis Layout Internet Statistics Computer vision Tracking Videoconference Shape |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition Software |
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