Transferring Adaptive Bit Rate Streaming Quality Models from H.264/HD to H.265/4K-UHD


IEICE TRANSACTIONS on Communications   Vol.E102-B   No.12   pp.2226-2242
Publication Date: 2019/12/01
Publicized: 2019/06/25
Online ISSN: 1745-1345
DOI: 10.1587/transcom.2019EBP3045
Type of Manuscript: PAPER
Category: Network
quality of experience,  adaptive bit rate streaming,  audiovisual-quality-estimation models,  subjective,  monitoring,  stalling,  

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In this paper the quality of adaptive bit rate video streaming is investigated and two state-of-the-art models, i.e., the NTT audiovisual quality-estimation and ITU-T P.1203 models, are considered. This paper shows how these models can be applied to new conditions, e.g., 4K ultra high definition (4K-UHD) videos encoded using H.265, considering that they were originally designed and trained for HD videos encoded with H.264. Six subjective evaluations involving up to 192 participants and a large variety of test conditions, e.g., durations from 10sec to 3min, coding-quality variation, and stalling events, were conducted on both TV and mobile devices. Using the subjective data, this paper addresses how models and coefficients can be transferred to new conditions. A comparison between state-of-the-art models is conducted, showing the performance of transferred and retrained models. It is found that other video-quality estimation models, such as VMAF, can be used as input of the NTT and ITU-T P.1203 long-term pooling modules, allowing these other video-quality-estimation models to support the specificities of adaptive bit-rate-streaming scenarios. Finally, all retrained coefficients are detailed in this paper allowing future work to directly reuse the results of this study.