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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xiaomeng Wu Satoh, S. |
| Copyright Year | 2011 |
| Description | Author affiliation: National Institute of Informatics, Digital Content and Media Sciences Research Division, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430, Japan (Xiaomeng Wu; Satoh, S.) |
| Abstract | We propose two novel algorithms for fully-unsupervised, super-fast, and cross-channel TV commercial mining in this paper. The tasks involved in the process include: 1) mining commercial clusters from streams of individual channels, and 2) grouping identical commercial clusters across multiple channels. The first process is achieved with a dual-stage hashing algorithm, which searches for recurring short segments by hashing frames, and it assembles these short segments into sets of commercial sequences by hashing temporal recurrences. The algorithm mined commercials from a one-month stream in less than 42 minutes, which was ten times faster than that in related studies. A new bag-of-fingerprints model is proposed for the second process to encode the temporal clues of local fingerprints. The model is abundantly robust against framing and fingerprinting errors in recurring sequences, and discovers false matches of local fingerprints. A five-month database was used for comprehensively demonstrating the effectiveness and efficiency of the model. |
| Starting Page | 2529 |
| Ending Page | 2532 |
| File Size | 286496 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781457713040 |
| ISSN | 15224880 |
| e-ISBN | 9781457713033 |
| e-ISBN | 9781457713026 |
| DOI | 10.1109/ICIP.2011.6116177 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-09-11 |
| Publisher Place | Belgium |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Streaming media Clustering algorithms Robustness Histograms TV Databases Conferences Duplicate Detection Fingerprinting |
| Content Type | Text |
| Resource Type | Article |
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