ML Anthology

Perspective Distortion Modeling, Learning and Compensation

Joachim Valente, Stefano Soatto
CVPRW 2015 pp. 9-16
doi:10.1109/CVPRW.2015.7301314 /cvprw/2015/valente2015cvprw-perspective/

Abstract

We describe a method to model perspective distortion as a one-parameter family of warping functions. This can be used to mitigate its effects on face recognition, or synthesis to manipulate the perceived characteristics of a face. The warps are learned from a novel dataset and, by comparing one-parameter families of images, instead of images themselves, we show the effects on face recognition, which are most significant when small focal lengths are used. Additional applications are presented to image editing, videoconference, and multi-view validation of recognition systems.

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Cite

Text

Valente and Soatto. "Perspective Distortion Modeling, Learning and Compensation." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2015. doi:10.1109/CVPRW.2015.7301314

Markdown

[Valente and Soatto. "Perspective Distortion Modeling, Learning and Compensation." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2015.](https://mlanthology.org/cvprw/2015/valente2015cvprw-perspective/) doi:10.1109/CVPRW.2015.7301314

BibTeX

@inproceedings{valente2015cvprw-perspective,
  title     = {{Perspective Distortion Modeling, Learning and Compensation}},
  author    = {Valente, Joachim and Soatto, Stefano},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2015},
  pages     = {9-16},
  doi       = {10.1109/CVPRW.2015.7301314},
  url       = {https://mlanthology.org/cvprw/2015/valente2015cvprw-perspective/}
}