Acceptability-Based QoE Models for Mobile Video
Acceptability-Based QoE Models for Mobile Video
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DOI：
10.1109/tmm.2014.2298217
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发表时间：
2014-04
影响因子：
7.3
通讯作者：
Wei Song;D. Tjondronegoro
中科院分区：
文献类型：
--
作者：
Wei Song;D. Tjondronegoro
体验质量（QoE）从主观用户体验和客观系统性能测量移动的视频递送的总体感知质量。目前的QoE预测模型有两个主要局限性：（1）对影响QoE的因素考虑不足，（2）对QoE模型可接受性预测的研究有限。在本文中，一组新的可接受性为基础的QoE模型，表示为A-QoE，提出了全面的用户研究的主观质量接受评估的结果的基础上。这些模型能够预测用户在各种移动的视频使用场景中的可接受性和愉悦度。采用统计非线性回归分析方法，以编码参数和比特率、视频内容特性、移动终端显示分辨率等因素作为独立预测因子，建立了视频质量预测模型。所提出的A-QoE模型的性能进行了比较，与三个著名的客观视频质量评估指标：PSNR，SSIM和VQM。所提出的A-QoE模型具有较高的预测精度和使用灵活性。未来以用户为中心的移动的视频传输系统可以从应用所提出的基于QoE的管理来优化视频编码和质量传输策略中受益。
Quality of experience (QoE) measures the overall perceived quality of mobile video delivery from subjective user experience and objective system performance. Current QoE prediction models have two main limitations: (1) insufficient consideration of the factors influencing QoE, and (2) limited studies on QoE models for acceptability prediction. In this paper, a set of novel acceptability-based QoE models, denoted as A-QoE, is proposed based on the results of comprehensive user studies on subjective quality acceptance assessments. The models are able to predict users' acceptability and pleasantness in various mobile video usage scenarios. Statistical nonlinear regression analysis has been used to build the models with a group of influencing factors as independent predictors, which include encoding parameters and bitrate, video content characteristics, and mobile device display resolution. The performance of the proposed A-QoE models has been compared with three well-known objective Video Quality Assessment metrics: PSNR, SSIM and VQM. The proposed A-QoE models have high prediction accuracy and usage flexibility. Future user-centred mobile video delivery systems can benefit from applying the proposed QoE-based management to optimize video coding and quality delivery strategies.