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December 30, 2002453 citations

A framework for the robust estimation of optical flow

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MBMichael J. BlackPAP. Anandan

Key Points

  • The aim is to develop a new framework for robustly estimating optical flow between image pairs while addressing common assumption violations.
  • Introduces a generalized line process for outlier management in optical flow estimation.
  • Demonstrates a graduated non-convexity algorithm for recovering optical flow and motion discontinuities.
  • Evaluates performance using both synthetic and natural images.
  • Successfully improves optical flow estimation in the presence of brightness and smoothness violations.
  • Achieved robust performance across different datasets, indicating the effectiveness of the framework.

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.>

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Cite This Study

Black et al. (2002) studied this question.

synapsesocial.com/papers/6a0e394a2a2e27e73427b695https://doi.org/10.1109/iccv.1993.378214
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