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Objective video quality evaluation incorporates spatial and temporal degradation effects to calculate quality grade for each video frame alone, as well as the overall quality grade for the whole sequence. Distortion visibility depends not only on the level of degradation but also on video content and viewer's preferences. Temporal pooling is a method that collapses series of frame quality scores to one quality score for whole video sequence and it should be aware of an influence of the video quality variation to the human overall judgments of quality. In this paper six pooling methods applied to five objective video quality metrics are compared. The best prediction capability has been obtained by those pooling methods that reflect two phenomena: a recency effect and the worst quality section influence. Moreover, the statistics of individual frames scores tends to be of high importance and strongly influences pooling method capabilities.Index Terms-video quality, subjective assessment, objective metrics, temporal pooling

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