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.
|Title of host publication||2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07|
|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||2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition|
|Period||17/06/07 → 22/06/07|