Principal Warps: Thin-Plate Splines and the Decomposition of Deformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Spline-Based Image Registration
International Journal of Computer Vision
Geometric Information Criterion for Model Selection
International Journal of Computer Vision
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Bayesian Model Estimation and Selection for Epipolar Geometry and Generic Manifold Fitting
International Journal of Computer Vision
A faster algorithm for ridge regression of reduced rank data
Computational Statistics & Data Analysis
Brownian Warps: A Least Committed Prior for Non-rigid Registration
MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part II
Fast Fluid Registration of Medical Images
VBC '96 Proceedings of the 4th International Conference on Visualization in Biomedical Computing
Consistent Nonlinear Elastic Image Registration
MMBIA '01 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA'01)
A minimum description length objective function for groupwise non-rigid image registration
Image and Vision Computing
Fast Non-Rigid Surface Detection, Registration and Realistic Augmentation
International Journal of Computer Vision
Special Issue on Tribute Workshop for Peter Johansen
Journal of Mathematical Imaging and Vision
International Journal of Computer Vision
In Vivo OCT Coronary Imaging Augmented with Stent Reendothelialization Score
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part I
Generalized Thin-Plate Spline Warps
International Journal of Computer Vision
Rejecting Mismatches by Correspondence Function
International Journal of Computer Vision
Monocular Template-based Reconstruction of Inextensible Surfaces
International Journal of Computer Vision
Feature-Based Deformable Surface Detection with Self-Occlusion Reasoning
International Journal of Computer Vision
WBIR'12 Proceedings of the 5th international conference on Biomedical Image Registration
In defence of RANSAC for outlier rejection in deformable registration
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
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Estimating smooth image warps from landmarks is an important problem in computer vision and medical image analysis. The standard paradigm is to find the model parameters by minimizing a compound energy including a data term and a smoother, balanced by a `smoothing parameter' that is usually fixed by trial and error.We point out that warp estimation is an instance of the general supervised machine learning problem of fitting a flexible model to data, and propose to learn the smoothing parameter while estimating the warp. The leading idea is to depart from the usual paradigm of minimizing the energy to the one of maximizing the predictivity of the warp, i.e. its ability to do well on the entire image, rather than only on the given landmarks. We use cross-validation to measure predictivity, and propose a complete framework to solve for the desired warp. We point out that the well-known non-iterative closed-form for the leave-one-out cross-validation score is actually a good approximation to the true score and show that it extends to the warp estimation problem by replacing the usual vector two-norm by the matrix Frobenius norm. Experimental results on real data show that the procedure selects sensible smoothing parameters, very close to user selected ones.