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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hung, Tzu-Yi Zhu, Ce Yang, Gao Tan, Yap-Peng |
| Copyright Year | 2012 |
| Description | Author affiliation: School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore (Hung, Tzu-Yi; Zhu, Ce; Yang, Gao; Tan, Yap-Peng) |
| Abstract | It is not uncommon to see several videos of almost identical content on the internet. These near duplicates, coupled with the sheer number of videos, pose a big challenge to the effective organization of video clips online. We propose an adaptive classification approach to detect near-duplicate versions, and an integrated voting strategy to group clusters and to elect a representative for each cluster. Our proposed methods are based on our observation that near-duplicate videos usually span a small, albeit variable area in the feature space, while videos of different contents are scattered far apart. The classification method aims to select a suitable threshold by maximizing the margin for each video sequence in the similarity space, and the voting scheme focuses on merging subsets with mutual information based on neighbor information and inverted indices. Experimental results on an unconstrained web dataset including over 10000 videos demonstrate the efficacy of the proposed methods. |
| Starting Page | 1879 |
| Ending Page | 1882 |
| File Size | 628894 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781467302180 |
| ISSN | 02714302 |
| e-ISBN | 9781467302197 |
| DOI | 10.1109/ISCAS.2012.6271637 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-05-20 |
| Publisher Place | Korea (South) |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Histograms Streaming media Feature extraction Indexes Vectors Color Clustering algorithms |
| Content Type | Text |
| Resource Type | Article |
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