Assesses optical flow estimation in images, suggesting improvements in accuracy and reliability.
The authors consider the problem of robustly estimating optical flow from a pair of images using a new framework based on robust estimation which addresses violations of the brightness constancy and spatial smoothness assumptions. They also show the relationship between the robust estimation framework and line-process approaches for coping with spatial discontinuities. In doing so, the notion of a line process is generalized to that of an outlier process that can account for violations in both the brightness and smoothness assumptions. A graduated non-convexity algorithm is presented for recovering optical flow and motion discontinuities. The performance of the robust formulation is demonstrated on both synthetic data and natural images.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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Black et al. (2002) studied this question.
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