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| Content Provider | ACM Digital Library |
|---|---|
| Author | Natsev, A. Adams, W. Neti, C. Naphade, M. Tseng, B. Smith, J. R. Lin, C-Y. Nock, H. J. |
| Abstract | This paper describes progress towards a general framework for incorporating multimodal cues into a trainable system for automatically annotating user-defined semantic concepts in broadcast video. Models of arbitrary concepts are constructed by building classifiers in a score space defined by a pre-deployed set of multimodal models. Results show annotation for user-defined concepts both in and outside the pre-deployed set is competitive with our best video-only models on the TREC Video 2002 corpus. An interesting side result shows speech-only models give performance comparable to our best video-only models for detecting visual concepts such as "outdoors", "face" and "cityscape". |
| Starting Page | 403 |
| Ending Page | 404 |
| Page Count | 2 |
| File Format | |
| ISBN | 1581136463 |
| DOI | 10.1145/860435.860522 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2003-07-28 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Acm proceedings Digital video annotation and indexing |
| Content Type | Text |
| Resource Type | Article |
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