LIVE-SJTU Audio and Video Quality Assessment (A/V-QA) Database
Description
The topics of visual and audio quality assessment (QA) have been widely researched for decades, yet nearly all of this prior work has focused only on single-mode visual or audio signals. However, visual signals rarely are presented without accompanying audio, including heavy-bandwidth video streaming applications. Moreover, the distortions that may separately (or conjointly) afflict the visual and audio signals collectively shape user-perceived quality of experience (QoE). This motivated us to conduct a subjective study of audio and video (A/V) quality, which we then used to compare and develop A/V quality measurement models and algorithms.
The new LIVE-SJTU Audio and Video Quality Assessment (A/V-QA) Database includes 14 reference and 336 distorted A/V sequences. Specifically, 24 distortion conditions generated from all possible combinations of 2 video distortion types with 4 distortion levels (video compression, video compression plus scaling), and 1 audio distortion type with 3 distortion levels (audio compression), were applied to the 14 reference A/V sequences, yielding a total of 336 distorted A/V sequences. We then conducted a subjective A/V quality perception study on the database towards attaining a better understanding of how humans perceive the overall combined quality of A/V signals.
All videos have resolutions of 1920×1080 pixels, and are provided in raw YUV 4:2:0 format. The frame rates of the 14 videos range from 24 to 29.97 frames per second, and all of the videos are of 8 seconds duration. The corresponding audio soundtracks are stereophonic audios with two channels which are provided in raw pulse-code modulation (PCM) format with a bit depth of 16 and a sampling rate of 48 kHz.
Investigators
The investigators in this research are:
Xiongkuo Min - PostDoc at Shanghai Jiao Tong University - email: minxiongkuo@gmail.com
Guangtao Zhai - Professor at Shanghai Jiao Tong University - email: zhaiguangtao@sjtu.edu.cn
Jiantao Zhou - Associate Professor at University of Macau - email: jtzhou@um.edu.mo
Mylène C. Q. Farias - Associate Professor at University of Brasilia - email: mylene@ieee.org
Alan Bovik
- Professor at UT Austin - email:
bovik@ece.utexas.edu
Download
We are making the LIVE-SJTU A/V-QA Database available to the research community free of charge. If you use this database in your research, we kindly ask that you reference our papers listed below:
- Xiongkuo Min, Guangtao Zhai, Jiantao Zhou, Mylène C. Q. Farias, and Alan Conrad Bovik, "Study of Subjective and Objective Quality Assessment of Audio-Visual Signals," IEEE Transactions on Image Processing, vol. 29, pp. 6054-6068, 2020.
- Xiongkuo Min, Guangtao Zhai, Jiantao Zhou, Mylène C. Q. Farias, and Alan Conrad Bovik, "LIVE-SJTU Audio and Video Quality Assessment Database", Online: http://live.ece.utexas.edu/research/avqa/index.html, 2020.
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Copyright Notice
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Copyright (c) 2019 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 images, 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:
- Xiongkuo Min, Guangtao Zhai, Jiantao Zhou, Mylène C. Q. Farias, and Alan Conrad Bovik, "Study of Subjective and Objective Quality Assessment of Audio-Visual Signals," IEEE Transactions on Image Processing, vol. 29, pp. 6054-6068, 2020.
- Xiongkuo Min, Guangtao Zhai, Jiantao Zhou, Mylène C. Q. Farias, and Alan Conrad Bovik, "LIVE-SJTU Audio and Video Quality Assessment Database", Online: http://live.ece.utexas.edu/research/avqa/index.html, 2020.
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