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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Liu, Jinjun Feng, Dan Hua, Yu Peng, Bin Zuo, Pengfei |
| Copyright Year | 2014 |
| Description | Author affiliation: Wuhan National Laboratory for Optoelectronics, School of Computer, Huazhong University of Science and Technology, Wuhan 430074, China (Liu, Jinjun; Feng, Dan; Hua, Yu; Peng, Bin; Zuo, Pengfei) |
| Abstract | With the wide use of video-editing software, more and more similar videos are uploaded to the video-sharing platforms in cloud storage. The large number of near-duplicate videos would not only make the users not satisfactory, but also consume more resources with service providers. Since the near-duplicate videos have redundancy at the content level, the traditional de-duplication technology is not suitable to address the redundancies. In order to decrease the redundancy, we proposed a novel high performance provenance-based video-sharing system, called Provis. Provis records the provenance of the videos and compresses the near-duplicate videos via storing their provenance which replaces storing their video files to improve the space efficiency. When users attempt to upload the edited videos, Provis can rebuild the videos in the cloud via collecting and uploading their provenance to reduce the network overhead of uploading videos. We implemented Provis and compared its performance with other existing video compression techniques. Our evaluation shows that Provis achieves significant space savings. |
| Starting Page | 1 |
| Ending Page | 8 |
| File Size | 156300 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781479975754 |
| DOI | 10.1109/PCCC.2014.7017097 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-12-05 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Videos Cloud computing Video compression Servers Indexes Redundancy |
| Content Type | Text |
| Resource Type | Article |
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