Autocalibration and uncalibrated reconstruction of shape from defocus

Yifei Lou, Paolo Favaro, Andrea L. Bertozzi, Stefano Soatto

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

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. © 2007 IEEE.

Original languageEnglish
Title of host publication2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07
DOIs
Publication statusPublished - 2007
Event2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Minneapolis, MN, United States
Duration: 17 Jun 200722 Jun 2007

Conference

Conference2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Abbreviated titleCVPR'07
CountryUnited States
CityMinneapolis, MN
Period17/06/0722/06/07

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  • Cite this

    Lou, Y., Favaro, P., Bertozzi, A. L., & Soatto, S. (2007). Autocalibration and uncalibrated reconstruction of shape from defocus. In 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07 https://doi.org/10.1109/CVPR.2007.383210