Abstract
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>
Keywords
Optical flowSmoothnessOutlierClassification of discontinuitiesBrightnessConvexityComputer scienceArtificial intelligenceRobustness (evolution)Process (computing)AlgorithmComputer visionMathematical optimizationMathematicsImage (mathematics)Mathematical analysis
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Publication Info
- Year
- 2002
- Type
- article
- Pages
- 231-236
- Citations
- 446
- Access
- Closed
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Cite This
Michael J. Black,
P. Anandan
(2002).
A framework for the robust estimation of optical flow.
, 231-236.
https://doi.org/10.1109/iccv.1993.378214
Identifiers
- DOI
- 10.1109/iccv.1993.378214