Computer Vision, Graphics, and Image Processing
A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Iterative point matching for registration of free-form curves and surfaces
International Journal of Computer Vision
Estimating 3-D rigid body transformations: a comparison of four major algorithms
Machine Vision and Applications - Special issue on performance evaluation
Self-Calibration of a Moving Camera from PointCorrespondences and Fundamental Matrices
International Journal of Computer Vision
Sequential Updating of Projective and Affine Structure from Motion
International Journal of Computer Vision
Area-based matching for simultaneous registration of multiple 3-D profile maps
Computer Vision and Image Understanding
Optimal Motion and Structure Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimating Motion and Structure from Correspondences of Line Segments between Two Perspective Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Calibration Errors in Structure from Motion
Mustererkennung 1998, 20. DAGM-Symposium
NRC '97 Proceedings of the International Conference on Recent Advances in 3-D Digital Imaging and Modeling
Geometric matching of 3D objects: assessing the range of successful initial configurations
NRC '97 Proceedings of the International Conference on Recent Advances in 3-D Digital Imaging and Modeling
The digital Michelangelo project: 3D scanning of large statues
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
A Maximum-Likelihood Surface Estimator for Dense Range Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
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A new method is proposed for refining the calibration of a light striping system including a projective transformation between the image plane of the camera and the plane of the laser sheet, and also the direction of the scanning with respect to the plane of the laser sheet. The refinement is obtained through weighted least squares matching of multiple profile maps acquired from different viewpoints and registered previously using an approximate calibration. Testing with synthetically generated profile maps shows that if the geometry of the object is appropriate and the registration parameters and the intrinsic parameters of the system are known exactly, then a calibration accuracy of 0.003 ... 0.00003% relative to the scene dimensions can be achieved as the average noise level in the maps used for the calibration decreases from 0.3 down to zero pixels. It is also possible to adjust several calibrations at the same time. The registration and calibration parameters can be refined simultaneously, but a close initial estimate and rather complex object geometry are needed for an accuracy of 0.03% when the average noise level is 0.03 pixels. Determining the corresponding points by interpolation on the parametric domains of the maps yields higher accuracy than perpendicular projection to the tangent planes at the closest points in 3-D in both registration and calibration tasks. The highest accuracy is achieved when the interpolation errors are as equal as possible within the overlapping areas.