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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Koz, A. Lagendijk, R.L. |
| Copyright Year | 2010 |
| Description | Author affiliation: Multimedia Signal Processing Group, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, The Netherlands (Koz, A.; Lagendijk, R.L.) |
| Abstract | Identification of a video file in current peer-to-peer (P2P) networks is achieved by its tag or by a (100–200 bits) cryptographic hash of the entire file. However, these approaches fail when the tag is changed or some small insertions, deletions or format changes are applied to the video by a user in the network. A complementary approach is to tag a video with a few hundreds of bits of information, which we call perceptual tags, extracted from perceptual features of the content robust to typical processing. In this paper, we first give the basic requirements for the extraction and distribution of these perceptual tags in a P2P network considering the characteristics of the peers (ordinary internet users), such as low computational power and low bandwidth. Then, we propose a novel method that extracts N (64–256) bits of robust perceptual tags for a video file by using only the mean of video frames. The proposed method also achieves the uniform distribution of perceptual tags among the peers needed for the state of the art DHT-based indexing implementations in P2P networks. |
| Starting Page | 193 |
| Ending Page | 196 |
| File Size | 124370 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424479924 |
| ISSN | 15224880 |
| e-ISBN | 9781424479948 |
| e-ISBN | 9781424479931 |
| DOI | 10.1109/ICIP.2010.5651094 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-09-26 |
| Publisher Place | Hong Kong |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Peer to peer computing Synchronization Histograms Robustness Feature extraction Indexing Tagging DHT Peer to Peer Perceptual Tags Content Search Access Right Management Video Identification |
| Content Type | Text |
| Resource Type | Article |
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