Alternative models for fish-eye lenses
Pattern Recognition Letters
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IEEE Transactions on Pattern Analysis and Machine Intelligence
A note on fitting great circles by least squares
Communications of the ACM
Machine Vision and Applications
Creating Image-Based VR Using a Self-Calibrating Fisheye Lens
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Estimation of omnidirectional camera model from epipolar geometry
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Equidistant (fθ) fish-eye perspective with application in distortion centre estimation
Image and Vision Computing
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Foundations and Trends® in Computer Graphics and Vision
A unified framework for line extraction in dioptric and catadioptric cameras
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part IV
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Fisheye lenses are often used to enlarge the field of view (FOV) of a conventional camera. But the images taken with fisheye lenses have severe distortions. This paper proposes a novel calibration method for fisheye lenses using images of space lines in a single fisheye image. Since some fisheye cameras’ FOV are around 180 degrees, the spherical perspective projection model is employed. It is well known that under spherical perspective projection, straight lines in space have to be projected into great circles in the spherical perspective image. That is called straight-line spherical perspective projection constraint (SLSPPC). In this paper, we use SLSPPC to determine the mapping between a fisheye image and its corresponding spherical perspective image. Once the mapping is obtained, the fisheye lenses is calibrated. The parameters to be calibrated include principal point, aspect ratio, skew factor, and distortion parameters. Experimental results for synthetic data and real images are presented to demonstrate the performances of our calibration algorithm.