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Improving the verification process of video quality metrics

机译:改进视频质量指标的验证过程

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The most important step in the development process of a video quality metric is its verification with regards to the subjective quality experience. Even though guidelines in the form of standards and recommendations are well known, there are still quite often shortcomings in the verification process of many metrics. In this contribution we revisit these rules, point out important details and review contributions to video quality metrics for typical shortcomings. We will highlight in detail five steps that should be followed in order to improve the overall quality of the verification process of video quality metrics: using a large and diverse data base, planing and conducting subjective tests carefully, using different data for calibration and verification of a metric, avoiding unnecessary data fitting steps, and a clear and meaningful presentation of the results. Also we will provide short examples how an improper verification might affect the results of a video quality metric.
机译:视频质量度量的开发过程中最重要的一步是其对主观质量体验的验证。尽管标准和建议形式的指导方针是众所周知的,但许多指标的验证过程中仍然存在相当常见的缺点。在这一贡献中,我们重新审视这些规则,指出了对典型缺点的重要细节和审查视频质量指标的贡献。我们将详细突出显示应遵循的五个步骤,以提高视频质量指标验证过程的整体质量:使用大型和多样化的数据库,仔细刨,使用不同的数据进行校准和验证的不同数据进行主观测试度量标准,避免不必要的数据拟合步骤,以及结果清晰而有意义的结果。此外,我们将提供简短的示例,如何影响视频质量度量的结果。

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