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Laboratory for Image & Video Engineering

Welcome to the LIVE Public-Domain Subjective Video Quality Database

LIVE Video Quality Assessment Database

Our paper won the IEEE Signal Processing Society Young Author Best Paper Award for 2013: http://www.signalprocessingsociety.org/uploads/awards/Young_Author_Best_Paper.pdf

Introduction

Quality assessment databases enable researchers to evaluate the performance of quality assessment algorithms and contribute towards attaining the ultimate goal of objective quality assessment research - matching human perception. LIVE has developed a video quality assessment database, that will supplement the LIVE Image Quality Database, to provide researchers with a much-needed tool to advance the state-of-the-art in objective video quality assessment.

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We are making the LIVE Video Quality 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:

  • K. Seshadrinathan, R. Soundararajan, A. C. Bovik and L. K. Cormack, "Study of Subjective and Objective Quality Assessment of Video", IEEE Transactions on Image Processing , vol.19, no.6, pp.1427-1441, June 2010.
  • K. Seshadrinathan, R. Soundararajan, A. C. Bovik and L. K. Cormack, "A Subjective Study to Evaluate Video Quality Assessment Algorithms", SPIE Proceedings Human Vision and Electronic Imaging , Jan. 2010.

Download information for the database may be obtained by contacting Kalpana Seshadrinathan (kalpana.seshadrinathan@ieee.org). Pre-prints of the papers are also available upon request, please contact Kalpana Seshadrinathan (kalpana.seshadrinathan@ieee.org).

Database Description

The goal of our study was to develop a database of videos that will challenge automatic VQA algorithms. The LIVE Video Quality Database uses ten uncompressed high-quality videos with a wide variety of content as reference videos. A set of 150 distorted videos were created from these reference videos (15 distorted videos per reference) using four different distortion types - - MPEG-2 compression, H.264 compression, simulated transmission of H.264 compressed bitstreams through error-prone IP networks and through error-prone wireless networks. Distortion strengths were adjusted manually taking care to ensure that the different distorted videos were separated by perceptual levels of distortion. Each video in the LIVE Video Quality Database was assessed by 38 human subjects in a single stimulus study with hidden reference removal, where the subjects scored the video quality on a continuous quality scale. The mean and variance of the Difference Mean Opinion Scores (DMOS) obtained from the subjective evaluations, along with the reference and distorted videos, are available as part of the database. We have also evaluated the performance of several full reference video quality assessment algorithms on the database and performed statistical tests on the results in our paper. See errata to the performance evaluation reported in our paper here .

Investigators

The investigators in this research are:

Copyright Notice

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Copyright (c) 2009 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 ) and Center for Perceptual Systems (CPS, http://www.cps.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:

  • K. Seshadrinathan, R. Soundararajan, A. C. Bovik and L. K. Cormack, "Study of Subjective and Objective Quality Assessment of Video", IEEE Transactions on Image Processing , vol.19, no.6, pp.1427-1441, June 2010.
  • K. Seshadrinathan, R. Soundararajan, A. C. Bovik and L. K. Cormack, "A Subjective Study to Evaluate Video Quality Assessment Algorithms", SPIE Proceedings Human Vision and Electronic Imaging , Jan. 2010.

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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