Autocalibration and uncalibrated reconstruction of shape from defocus

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

doi:10.1109/CVPR.2007.383210

Autocalibration and uncalibrated reconstruction of shape from defocus

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

School of Engineering & Physical Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 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 language	English
Title of host publication	2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07
DOIs	https://doi.org/10.1109/CVPR.2007.383210
Publication status	Published - 2007
Event	2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Minneapolis, MN, United States Duration: 17 Jun 2007 → 22 Jun 2007

Conference

Conference	2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Abbreviated title	CVPR'07
Country/Territory	United States
City	Minneapolis, MN
Period	17/06/07 → 22/06/07

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10.1109/CVPR.2007.383210

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@inproceedings{cf37e22d5c21437e89daa62841a0ff7c,

title = "Autocalibration and uncalibrated reconstruction of shape from defocus",

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. {\textcopyright} 2007 IEEE.",

author = "Yifei Lou and Paolo Favaro and Bertozzi, {Andrea L.} and Stefano Soatto",

year = "2007",

doi = "10.1109/CVPR.2007.383210",

language = "English",

isbn = "1424411807",

booktitle = "2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07",

note = "2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07 ; Conference date: 17-06-2007 Through 22-06-2007",

}

Lou, Y, Favaro, P, Bertozzi, AL & 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. 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Minneapolis, MN, United States, 17/06/07. https://doi.org/10.1109/CVPR.2007.383210

TY - GEN

T1 - Autocalibration and uncalibrated reconstruction of shape from defocus

AU - Lou, Yifei

AU - Favaro, Paolo

AU - Bertozzi, Andrea L.

AU - Soatto, Stefano

PY - 2007

Y1 - 2007

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=35148863127&partnerID=8YFLogxK

U2 - 10.1109/CVPR.2007.383210

DO - 10.1109/CVPR.2007.383210

M3 - Conference contribution

SN - 1424411807

SN - 9781424411801

BT - 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07

T2 - 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Y2 - 17 June 2007 through 22 June 2007

ER -

Autocalibration and uncalibrated reconstruction of shape from defocus

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