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Multi-Profile Ultra High Definition (UHD) AVC and HEVC 4K DASH Datasets 

 

We kindly ask that should you mention any of our datasets, or use our code, in your publication, that you would reference the following paper:

J.J. Quinlan, C.J. Sreenan. "Multi-Profile Ultra High Definition (UHD) AVC and HEVC 4K DASH Datasets". In Proceedings of ACM Multimedia Systems Conference (MMSys 2018), Amsterdam, The Netherlands, June 12 - 15, 2018.  Further details on our datasets are available in the conference paper. 

The following outlines the various files and scripts to use our UHD 4K Datasets. The clip names to acronyms are Big Buck Bunny (bbb), Sintel (sintel) and and Tears of Steel (tos). While x264 denotes AVC and x265 equates to HEVC.

Testbed Dataset - The following tables provides links to the MPD files for each of the clips, grouped per DASH profile.

FULL DASH Profile:

2-second segment 4-second segment 6-second segment 8-second segment 10-second segment


MAIN DASH Profile:

2-second segment 4-second segment 6-second segment 8-second segment 10-second segment


LIVE DASH Profile:

2-second segment 4-second segment 6-second segment 8-second segment 10-second segment


FULL Byte Range DASH Profile:

2-second segment 4-second segment 6-second segment 8-second segment 10-second segment


MAIN Byte Range DASH Profile:

2-second segment 4-second segment 6-second segment 8-second segment 10-second segment


onDEMAND Byte Range DASH Profile:

2-second segment 4-second segment 6-second segment 8-second segment 10-second segment

 

The 4K Segment Distribution files can be found . The DASH profiles contained in the 4K Segment Distribution files are "main", "live" and "full". These files can be used for trace-based simulation using NS-3 or similar network simulators.

The zipped pre-DASH MP4 files can be found . The MP4 files are zipped per individual clip, based on a folder structure of segment_duration/encoder/clip While the bash script to create the DASH profiles from these MP4 files can be found

A VirtualBox VM of Ubuntu 16.04, containing all the open-source programs needed to stream our 4K Dataset is available

 

Enjoy, Jason (j.quinlan@cs.ucc.ie)

 

This work has emanated from research conducted with the financial support of Science Foundation Ireland (SFI) under Grant Number 13/IA/1892.

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