Temporal quality assessment for mobile videos
Proceedings of the 18th annual international conference on Mobile computing and networking
Visual saliency and distortion weighting based video quality assessment
PCM'12 Proceedings of the 13th Pacific-Rim conference on Advances in Multimedia Information Processing
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We propose a new video quality assessment (VQA) algorithm - the motion compensated structural similarity index - that assesses not only spatial quality but also quality along temporal trajectories. Drawing inspiration from the motion-compensated approach followed for video compression, we propose a motion-compensated approach to temporal quality assessment. The proposed algorithm is computationally efficient as compared to other VQA algorithms that utilize motion information from extracted optical flow and correlates well with human perception of quality. In order to exemplify the utility of the algorithm in a practical setting, we evaluate the quality of H.264/AVC compressed videos. Efficiency of computation is enabled by the novel motion-vector re-use concept.