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The robust estimation of multiple motions: parametric and piecewise-smooth flow fields
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A Pixel Dissimilarity Measure That Is Insensitive to Image Sampling
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Multiple view geometry in computer visiond
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Video matting of complex scenes
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This paper describes a method for bringing two videos (recorded at different times) into spatiotemporal alignment, then comparing and combining corresponding pixels for applications such as background subtraction, compositing, and increasing dynamic range. We align a pair of videos by searching for frames that best match according to a robust image registration process. This process uses locally weighted regression to interpolate and extrapolate high-likelihood image correspondences, allowing new correspondences to be discovered and refined. Image regions that cannot be matched are detected and ignored, providing robustness to changes in scene content and lighting, which allows a variety of new applications.