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The Outlier Process: Unifying Line Processes and Robust Statistics

Michael J. Black, Anand Rangarajan
CVPR 1994 pp. 15-22
doi:10.1109/CVPR.1994.323805 /cvpr/1994/black1994cvpr-outlier/

Abstract

This paper unifies "line-process" approaches for regularization with discontinuities and robust estimation techniques. We generalize the notion of a "line process" to that of an analog "outlier process" and show that a problem formulated in terms of outlier processes can be viewed in terms of robust statistics. We also characterize a class of robust statistical problems for which an equivalent outlier-process formulation exists and give a straightforward method for converting a robust estimation problem into an outlier-process formulation. This outlier-processes approach provides a general framework which subsumes the traditional line-process approaches as well as a wide class of robust estimation problems. Examples in image reconstruction and optical flow are used to illustrate the approach.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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Cite

Text

Black and Rangarajan. "The Outlier Process: Unifying Line Processes and Robust Statistics." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1994. doi:10.1109/CVPR.1994.323805

Markdown

[Black and Rangarajan. "The Outlier Process: Unifying Line Processes and Robust Statistics." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1994.](https://mlanthology.org/cvpr/1994/black1994cvpr-outlier/) doi:10.1109/CVPR.1994.323805

BibTeX

@inproceedings{black1994cvpr-outlier,
  title     = {{The Outlier Process: Unifying Line Processes and Robust Statistics}},
  author    = {Black, Michael J. and Rangarajan, Anand},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1994},
  pages     = {15-22},
  doi       = {10.1109/CVPR.1994.323805},
  url       = {https://mlanthology.org/cvpr/1994/black1994cvpr-outlier/}
}