Autocalibration and Uncalibrated Reconstruction of Shape from Defocus
Yifei Lou
Favaro, P.
Bertozzi, A.L.
Soatto, S.
Univ. of California Los Angeles, Los Angeles;
This paper appears in: Computer Vision and Pattern Recognition, 2007. CVPR '07. IEEE Conference on
Publication Date: 17-22 June 2007
On page(s): 1-8
Location: Minneapolis, MN,
ISBN: 1-4244-1180-7
INSPEC Accession Number: 9738099
Digital Object Identifier: 10.1109/CVPR.2007.383210
Current Version Published: 2007-07-16
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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