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
Rigid, affine and locally affine registration of free-form surfaces
International Journal of Computer Vision
Algorithm 813: SPG—Software for Convex-Constrained Optimization
ACM Transactions on Mathematical Software (TOMS)
Reconstruction of Three-Dimensional Objects through Matching of Their Parts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Partial matching of 3D shapes with priority-driven search
SGP '06 Proceedings of the fourth Eurographics symposium on Geometry processing
Laplace-Beltrami eigenfunctions for deformation invariant shape representation
SGP '07 Proceedings of the fifth Eurographics symposium on Geometry processing
Regularized Partial Matching of Rigid Shapes
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
Parametric estimation of affine deformations of planar shapes
Pattern Recognition
International Journal of Computer Vision
A correspondence-less approach to matching of deformable shapes
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
Putting the pieces together: regularized multi-part shape matching
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part I
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This paper is addressing the problem of realigning broken objects without correspondences. We consider linear transformations between the object fragments and present the method through 2D and 3D affine transformations. The basic idea is to construct and solve a polynomial system of equations which provides the unknown parameters of the alignment. We have quantitatively evaluated the proposed algorithm on a large synthetic dataset containing 2D and 3D images. The results show that the method performs well and robust against segmentation errors. We also present experiments on 2D real images as well as on volumetric medical images applied to surgical planning.