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  • Blind video temporal consis...
    Bonneel, Nicolas; Tompkin, James; Sunkavalli, Kalyan; Sun, Deqing; Paris, Sylvain; Pfister, Hanspeter

    ACM transactions on graphics, 11/2015, Letnik: 34, Številka: 6
    Journal Article

    Extending image processing techniques to videos is a non-trivial task; applying processing independently to each video frame often leads to temporal inconsistencies, and explicitly encoding temporal consistency requires algorithmic changes. We describe a more general approach to temporal consistency. We propose a gradient-domain technique that is blind to the particular image processing algorithm. Our technique takes a series of processed frames that suffers from flickering and generates a temporally-consistent video sequence. The core of our solution is to infer the temporal regularity from the original unprocessed video, and use it as a temporal consistency guide to stabilize the processed sequence. We formally characterize the frequency properties of our technique, and demonstrate, in practice, its ability to stabilize a wide range of popular image processing techniques including enhancement and stylization of color and tone, intrinsic images, and depth estimation.