ML Anthology

Autocalibration and Uncalibrated Reconstruction of Shape from Defocus

Yifei Lou, Paolo Favaro, Andrea L. Bertozzi, Stefano Soatto
CVPR 2007
doi:10.1109/CVPR.2007.383210 /cvpr/2007/lou2007cvpr-autocalibration/

Abstract

Most algorithms for reconstructing shape from defocus assume that the images are obtained with a camera that has been previously calibrated so that the aperture, focal plane, and focal length are known. In this manuscript we characterize the set of scenes that can be reconstructed from defocused images regardless of calibration parameters. In lack of knowledge about the camera or about the scene, reconstruction is possible only up to an equivalence class that is described analytically. When weak knowledge about the scene is available, however, we show how it can be exploited in order to auto-calibrate the imaging device. This includes imaging a slanted plane or generic assumptions on the restoration of the deblurred images.

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Cite

Text

Lou et al. "Autocalibration and Uncalibrated Reconstruction of Shape from Defocus." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2007. doi:10.1109/CVPR.2007.383210

Markdown

[Lou et al. "Autocalibration and Uncalibrated Reconstruction of Shape from Defocus." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2007.](https://mlanthology.org/cvpr/2007/lou2007cvpr-autocalibration/) doi:10.1109/CVPR.2007.383210

BibTeX

@inproceedings{lou2007cvpr-autocalibration,
  title     = {{Autocalibration and Uncalibrated Reconstruction of Shape from Defocus}},
  author    = {Lou, Yifei and Favaro, Paolo and Bertozzi, Andrea L. and Soatto, Stefano},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2007},
  doi       = {10.1109/CVPR.2007.383210},
  url       = {https://mlanthology.org/cvpr/2007/lou2007cvpr-autocalibration/}
}