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| Content Provider | ACM Digital Library |
|---|---|
| Author | Snoek, Cees G. M. Hauptmann, Alexander G. Worring, Marcel |
| Copyright Year | 2006 |
| Abstract | We propose a generic and robust framework for news video indexing which we founded on a broadcast news production model. We identify within this model four production phases, each providing useful metadata for annotation. In contrast to semiautomatic indexing approaches which exploit this information at production time, we adhere to an automatic data-driven approach. To that end, we analyze a digital news video using a separate set of multimodal detectors for each production phase. By combining the resulting production-derived features into a statistical classifier ensemble, the framework facilitates robust classification of several $\textit{rich}$ semantic concepts in news video; rich meaning that concepts share many similarities in their production process. Experiments on an archive of 120 hours of news video from the 2003 TRECVID benchmark show that a combined analysis of production phases yields the best results. In addition, we demonstrate that the accuracy of the proposed style analysis framework for classification of several rich semantic concepts is state-of-the-art. |
| Starting Page | 91 |
| Ending Page | 108 |
| Page Count | 18 |
| File Format | |
| ISSN | 15516857 |
| e-ISSN | 15516865 |
| DOI | 10.1145/1142020.1142021 |
| Volume Number | 2 |
| Issue Number | 2 |
| Journal | ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2006-05-01 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Benchmark evaluation Multimedia understanding Multimodal detectors News video indexing Semantic classification Statistical pattern recognition Style analysis |
| Content Type | Text |
| Resource Type | Article |
| Subject | Hardware and Architecture Computer Networks and Communications |
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