Welcome to the LIVE-APV Livestream Video Quality Assessment Database
LIVE-APV Livestream Video Quality Assessment Database
Video live streaming is gaining prevalence among video streaming services, especially for the delivery of popular sporting events. The quality of these live streaming videos can be adversely affected by any of a wide variety of events,including poor network connections, capture artifacts, and distortions incurred during coding and transmission. Because of this, the development of objective Video Quality Assessment (VQA) algorithms that can predict the perceptual quality of videos have become important sources of feedback, monitoring, and control of video streaming. Important resources for developing these algorithms are appropriate databases that exemplify the kinds of live streaming video distortions encountered in practice. Towards making progress in this direction, we built a video quality database specifically designed for live streaming VQA research. The new video database is called the Laboratory for Image and Video Engineering - Amazon Prime Video (APV) Live Video Streaming Database (LIVE-APV). We envision that researchers will find the dataset to be useful for the development, testing, and comparison of future VQA models.
We are making the LIVE-APV Livestream Video Quality Assessment Database available to the research community free of charge. If you use this database in your research, we kindly ask that you to cite our paper listed below:
- Z. Shang, J.P. Ebenezer, Y. Wu, H. Wei, S. Sethuraman, and A. C. Bovik, “Study of Subjective and Objective Quality of LiveStreaming Sports Videos,” 2020
You can download the publicly available release of the database by filling THIS form. The password and link to the database will be sent to you once you complete the form.
LIVE-APV includes 367 videos of 97 contents impaired by 7 types of distortions. We performed a subjective quality study using the new database, whereby more than 14,000 human opinions were gathered from 40 subjects. All videos were of native 4K content or upscaled to 4K, and were shown on a 4K TV. We demonstrate the usefulness of the new resource by performing a holistic evaluation of the performance of current state-of-the-art (SOTA) VQA models.
The investigators in this research are:
- Zaixi Shang ( email@example.com ) -- Graduate student, Dept. of ECE, UT Austin.
- Joshua Ebenezer ( firstname.lastname@example.org ) -- Graduate student, Dept. of ECE, UT Austin.
- Yongjun Wu ( email@example.com ) Amazon Prime Video, Seattle, WA
- Hai Wei ( firstname.lastname@example.org ) Amazon Prime Video, Seattle, WA
- Sriram Sethuraman ( email@example.com ) Amazon Prime Video, Seattle, WA
- Alan C. Bovik ( firstname.lastname@example.org ) -- Professor, Dept. of ECE, UT Austin
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Copyright (c) 2016 The University of Texas at Austin
All rights reserved.
Permission is hereby granted, without written agreement and without license or royalty fees, to use, copy, modify, and distribute this database (the videos, the results and the source files) and its documentation for any purpose, provided that the copyright notice in its entirety appear in all copies of this database, and the original source of this database, Laboratory for Image and Video Engineering (LIVE, http://live.ece.utexas.edu ) at the University of Texas at Austin (UT Austin, http://www.utexas.edu ), is acknowledged in any publication that reports research using this database.
The following papers are to be cited in the bibliography whenever the database is used as:
- Z. Shang, J. P. Ebenezer, Y. Wu, H. Wei, S. Sethuraman and A. C. Bovik, "Study of the Subjective and Objective Quality of High Motion Live Streaming Videos," in IEEE Transactions on Image Processing, vol. 31, pp. 1027-1041, 2022, doi: 10.1109/TIP.2021.3136723.
- Z. Shang, J. P. Ebenezer, A. C. Bovik, Y. Wu, H. Wei and S. Sethuraman, "Assessment of Subjective and Objective Quality of Live Streaming Sports Videos," 2021 Picture Coding Symposium (PCS), 2021, pp. 1-5, doi: 10.1109/PCS50896.2021.9477502.
- Z. Shang, J.P. Ebenezer, Y. Wu, H. Wei, S. Sethuraman, and A. C. Bovik, "LIVE-APV Live Video Streaming Database," Online: http://live.ece.utexas.edu/research/LIVE_APV_Study/apv_index.html, 2020.
IN NO EVENT SHALL THE UNIVERSITY OF TEXAS AT AUSTIN BE LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE USE OF THIS DATABASE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF TEXAS AT AUSTIN HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
THE UNIVERSITY OF TEXAS AT AUSTIN SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE DATABASE PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF TEXAS AT AUSTIN HAS NO OBLIGATION TO PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
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