On the accuracy of video quality measurement techniques

With the massive growth of Internet video streaming, it is critical to accurately measure video quality subjectively and objectively, especially HD and UHD video which is bandwidth intensive. We summarize the creation of a database of 200 clips, with 20 unique sources tested across a variety of devices. By classifying the test videos into 2 distinct quality regions SD and HD, we show that the high correlation claimed by objective video quality metrics is led mostly by videos in the SD quality region. We perform detailed correlation analysis and statistical hypothesis testing of the HD subjective quality scores, and establish that the commonly used ACR methodology of subjective testing is unable to capture significant quality differences, leading to poor measurement accuracy for both subjective and objective metrics even on large-screen display devices.

[1]  Mohamed-Chaker Larabi,et al.  Influence of video resolution, viewing device and audio quality on perceived multimedia quality for steaming applications , 2014, 2014 5th European Workshop on Visual Information Processing (EUVIP).

[2]  Fan Zhang,et al.  Image Quality Assessment by Separately Evaluating Detail Losses and Additive Impairments , 2011, IEEE Transactions on Multimedia.

[3]  Alan C. Bovik,et al.  Image information and visual quality , 2006, IEEE Trans. Image Process..

[4]  Gustavo E. A. P. A. Batista,et al.  A study of the behavior of several methods for balancing machine learning training data , 2004, SKDD.

[5]  Patrick Le Callet,et al.  Quantifying the Influence of Devices on Quality of Experience for Video Streaming , 2018, 2018 Picture Coding Symposium (PCS).

[6]  Alan C. Bovik,et al.  A Simple Prediction Fusion Improves Data-driven Full-Reference Video Quality Assessment Models , 2018, 2018 Picture Coding Symposium (PCS).

[7]  Andrew Catellier,et al.  Impact of mobile devices and usage location on perceived multimedia quality , 2012, 2012 Fourth International Workshop on Quality of Multimedia Experience.

[8]  Margaret H. Pinson,et al.  Techniques for Evaluating Objective Video Quality Models Using Overlapping Subjective Data Sets , 2008 .

[9]  Reza Rassool,et al.  VMAF reproducibility: Validating a perceptual practical video quality metric , 2017, 2017 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB).

[10]  Alan C. Bovik,et al.  Mean squared error: Love it or leave it? A new look at Signal Fidelity Measures , 2009, IEEE Signal Processing Magazine.

[11]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[12]  Christian Keimel,et al.  Influence of viewing device and soundtrack in HDTV on subjective video quality , 2011, Electronic Imaging.

[13]  Margaret H. Pinson,et al.  Comparing subjective video quality testing methodologies , 2003, Visual Communications and Image Processing.

[14]  Zhengfang Duanmu,et al.  A Quality-of-Experience Index for Streaming Video , 2017, IEEE Journal of Selected Topics in Signal Processing.

[15]  Zhou Wang,et al.  Multi-scale structural similarity for image quality assessment , 2003 .