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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Van Kets, N. De Praeter, J. Van Wallendael, G. De Cock, J. Van de Walle, R. |
| Copyright Year | 2015 |
| Description | Author affiliation: Multimedia Lab., Ghent Univ., Ghent, Belgium (Van Kets, N.; De Praeter, J.; Van Wallendael, G.; De Cock, J.; Van de Walle, R.) |
| Abstract | Broadcast providers are looking for new opportunities to increase user experience and user interaction on their content. Their main goal is to attract and preserve viewer attention to create a big and stable audience. This could be achieved with a second screen application that lets the users select their own viewpoint in an extremely high resolution video to direct their own first screen. By allowing the users to create their own personalized video stream, they become involved with the content creation itself. However, encoding a personalized view for each user is computationally complex. This paper describes a machine learning approach to speed up the encoding of each personal view. Simulation results of zoom, pan and tilt scenarios show bit rate increases between 2% and 9% for complexity reductions between 69% and 79% compared to full encoding. |
| Starting Page | 1 |
| Ending Page | 7 |
| File Size | 824727 |
| Page Count | 7 |
| File Format | |
| ISBN | 9781479958658 |
| DOI | 10.1109/BMSB.2015.7177225 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-06-17 |
| Publisher Place | Belgium |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | High Efficiency Video Coding (HEVC) Transforms video interaction Future technologies and services of broadcasting Cameras Encoding Complexity theory High definition video machine learning Spatial resolution video coding and processing |
| Content Type | Text |
| Resource Type | Article |
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