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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Lezi Wang Yuan Dong Hongliang Bai Jiwei Zhang Chong Huang Wei Liu |
| Copyright Year | 2012 |
| Abstract | The exponential growth of web videos brings content based copy detection into a crucial issue. Besides the image information, audio also plays an important role in copy detection. In this paper, the audio-based copy detection framework is introduced. Three contributions are presented: (1) the band energy difference based feature is improved by adding multi-scale information, which extends the candidate feature sets, (2) a conditional entropy based method is used to select 16 ordinal relations to generate a more compact and robust feature combination among the random $C_{91}^{16}\approx2.6\times10^{17}$ combinations, (3) the result-based fusion strategy is introduced to recall the missed true positives. The proposed algorithm outperforms the traditional coarse fingerprints, shown by experiments conducted in the TRECVID 2011 Content-based Copy Detection (CCD) database. |
| Starting Page | 961 |
| Ending Page | 966 |
| File Size | 424779 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781467316590 |
| ISSN | 19457871 |
| DOI | 10.1109/ICME.2012.17 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-07-09 |
| Publisher Place | Australia |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Feature extraction Videos Indexing Entropy Robustness Compounds Contend-based Copy Detection Conditional Entropy Fusion Audio TRECVID |
| Content Type | Text |
| Resource Type | Article |
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