Direct least-squares fitting of algebraic surfaces
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonmetric Calibration of Wide-Angle Lenses and Polycameras
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine Vision and Applications
Lens distortion calibration using point correspondences
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Nonmetric Lens Distortion Calibration: Closed-form Solutions, Robust Estimation and Model Selection
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Least Squares Fitting of Circles
Journal of Mathematical Imaging and Vision
Fundamental Matrix for Cameras with Radial Distortion
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Parameter-Free Radial Distortion Correction with Center of Distortion Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A new calibration model of camera lens distortion
Pattern Recognition
An Algebraic Approach to Lens Distortion by Line Rectification
Journal of Mathematical Imaging and Vision
A Simple Method of Radial Distortion Correction with Centre of Distortion Estimation
Journal of Mathematical Imaging and Vision
A VLSI implementation of barrel distortion correction for wide-angle camera images
IEEE Transactions on Circuits and Systems II: Express Briefs
Generic self-calibration of central cameras
Computer Vision and Image Understanding
Camera distortion self-calibration using the plumb-line constraint and minimal Hough entropy
Machine Vision and Applications
Robust radial distortion from a single image
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part II
A Minimal Solution to Radial Distortion Autocalibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automated center of radial distortion estimation, using active targets
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part II
Pattern Recognition Letters
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Many computer vision algorithms rely on the assumptions of the pinhole camera model, but lens distortion with off-the-shelf cameras is usually significant enough to violate this assumption. Many methods for radial distortion estimation have been proposed, but they all have limitations. Robust automatic radial distortion estimation from a single natural image would be extremely useful for many applications, particularly those in human-made environments containing abundant lines. For example, it could be used in place of an extensive calibration procedure to get a mobile robot or quadrotor experiment up and running quickly in an indoor environment. We propose a new method for automatic radial distortion estimation based on the plumb-line approach. The method works from a single image and does not require a special calibration pattern. It is based on Fitzgibbon's division model, robust estimation of circular arcs, and robust estimation of distortion parameters. We perform an extensive empirical study of the method on synthetic images. We include a comparative statistical analysis of how different circle fitting methods contribute to accurate distortion parameter estimation. We finally provide qualitative results on a wide variety of challenging real images. The experiments demonstrate the method's ability to accurately identify distortion parameters and remove distortion from images.