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Capturing Video Frame Rate Variations via Entropic Differencing

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Document pages: 5 pages

Abstract: High frame rate videos are increasingly getting popular in recent years,driven by the strong requirements of the entertainment and streaming industriesto provide high quality of experiences to consumers. To achieve the besttrade-offs between the bandwidth requirements and video quality in terms offrame rate adaptation, it is imperative to understand the effects of frame rateon video quality. In this direction, we devise a novel statistical entropicdifferencing method based on a Generalized Gaussian Distribution modelexpressed in the spatial and temporal band-pass domains, which measures thedifference in quality between reference and distorted videos. The proposeddesign is highly generalizable and can be employed when the reference anddistorted sequences have different frame rates. Our proposed model correlatesvery well with subjective scores in the recently proposed LIVE-YT-HFR databaseand achieves state of the art performance when compared with existingmethodologies.

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