IEEE Transactions on Broadcasting, vol.60, no.4, pp.637-649, Dec. 2014
Margaret H. Pinson; Lark Kwon Choi; Alan Conrad Bovik
Abstract: We announce a new Video Quality Model (VQM) that accounts for the perceptual impact of variable frame delays (VFD) in videos with demonstrated top performance on the Laboratory for Image & Video Engineering (LIVE) Mobile Video Quality Assessment (VQA) database. This model, called VQM_VFD, uses perceptual features extracted from spatial-temporal blocks spanning fixed angular extents and a long edge detection filter. VQM_VFD predicts video quality by measuring multiple frame delays using perception based parameters to track subjective quality over time. In the performance analysis of VQM_VFD, we evaluated its efficacy at predicting human opinions of visual quality. A detailed correlation analysis and statistical hypothesis testing show that VQM_VFD accurately predicts human subjective judgments and substantially outperforms top-performing Image Quality Assessment (IQA) and VQA models previously tested on the LIVE Mobile VQA database. VQM_VFD achieved the best performance on the mobile and tablet studies of the LIVE Mobile VQA database for simulated compression, wireless packet-loss, and rate adaptation, but not for temporal dynamics. These results validate the new model and warrant a hard release of the VQM_VFD algorithm. It is freely available for any purpose, commercial, or noncommercial at https://www.its.ntia.gov/vqm/.
Keywords: video quality model; video quality assessment; variable frame delay; edge detection; VQM_VFD
For technical information concerning this report, contact:
Margaret H. Pinson
Institute for Telecommunication Sciences
Disclaimer: Certain commercial equipment, components, and software may be identified in this report to specify adequately the technical aspects of the reported results. In no case does such identification imply recommendation or endorsement by the National Telecommunications and Information Administration, nor does it imply that the equipment or software identified is necessarily the best available for the particular application or uses.