Projective Structure from Uncalibrated Images: Structure From Motion and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimation of Relative Camera Positions for Uncalibrated Cameras
ECCV '92 Proceedings of the Second European Conference on Computer Vision
What can be seen in three dimensions with an uncalibrated stereo rig
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Novel view synthesis in tensor space
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Metric calibration of a stereo rig
VSR '95 Proceedings of the IEEE Workshop on Representation of Visual Scenes
In defence of the 8-point algorithm
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Accurate internal camera calibration using rotation, with analysis of sources of error
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Estimating vignetting function from a single image for image authentication
Proceedings of the 12th ACM workshop on Multimedia and security
Modeling and synthesis of aperture effects in cameras
Computational Aesthetics'08 Proceedings of the Fourth Eurographics conference on Computational Aesthetics in Graphics, Visualization and Imaging
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In this paper, we show that it is possible to calibrate a camera using just a flat, textureless Lambertian surface and constant illumination. This is done using the effects of off-axis illumination and vignetting, which result in reduction of light into the camera at off-axis angles. We use these imperfections to our advantage. The intrinsic parameters that we consider are the focal length, principal point, aspect ratio, and skew. We also consider the effect of the tilt of the camera. Preliminary results from simulated and real experiments show that the focal length can be recovered relatively robustly under certain conditions