HYPER: A New Approach for the Recognition and Positioning of Two-Dimensional Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Least-Squares Fitting of Two 3-D Point Sets
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the representation and estimation of spatial uncertainly
International Journal of Robotics Research
Computer Vision, Graphics, and Image Processing
Parameter estimation and hypothesis testing in linear models
Parameter estimation and hypothesis testing in linear models
A stochastic map for uncertain spatial relationships
Proceedings of the 4th international symposium on Robotics Research
IEEE Transactions on Pattern Analysis and Machine Intelligence
Model-based object recognition by geometric hashing
ECCV 90 Proceedings of the first european conference on Computer vision
Object recognition by computer: the role of geometric constraints
Object recognition by computer: the role of geometric constraints
Least-Squares Estimation of Transformation Parameters Between Two Point Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust regression methods for computer vision: a review
International Journal of Computer Vision
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
Geometric computation for machine vision
Geometric computation for machine vision
Iterative point matching for registration of free-form curves and surfaces
International Journal of Computer Vision
Computing the differential characteristics of isointensity surface
Computer Vision and Image Understanding
3D-2D projective registration of free-form curves and surfaces
Computer Vision and Image Understanding
Integration, Coordination and Control of Multi-Sensor Robot Systems
Integration, Coordination and Control of Multi-Sensor Robot Systems
Artificial Vision for Mobile Robots: Stereo Vision and Multisensory Perception
Artificial Vision for Mobile Robots: Stereo Vision and Multisensory Perception
Analysis of 3-D Rotation Fitting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust 3-D-3-D Pose Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Randomness and Geometric Features in Computer Vision
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Validation of 3-D registration methods based on points and frames
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Uniform Distribution, Distance and Expectation Problems for Geometric Features Processing
Journal of Mathematical Imaging and Vision
Medical Image Registration Using Geometric Hashing
IEEE Computational Science & Engineering
Special issue on registration and fusion of range images
Computer Vision and Image Understanding - Registration and fusion of range images
IPMI '99 Proceedings of the 16th International Conference on Information Processing in Medical Imaging
Gauge Independence in Optimization Algorithms for 3D Vision
ICCV '99 Proceedings of the International Workshop on Vision Algorithms: Theory and Practice
Bootstrapping Errors-in-Variables Models
ICCV '99 Proceedings of the International Workshop on Vision Algorithms: Theory and Practice
Rigid Point-Surface Registration Using an EM Variant of ICP for Computer Guided Oral Implantology
MICCAI '01 Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention
Spline-based elastic image registration: integration of landmark errors and orientation attributes
Computer Vision and Image Understanding
A Riemannian Framework for Tensor Computing
International Journal of Computer Vision
Intrinsic Statistics on Riemannian Manifolds: Basic Tools for Geometric Measurements
Journal of Mathematical Imaging and Vision
Robotics and Autonomous Systems
Kalman Filtering for Frame-by-Frame CT to Ultrasound Rigid Registration
MIAR '08 Proceedings of the 4th international workshop on Medical Imaging and Augmented Reality
Simulation of Ground-Truth Validation Data Via Physically- and Statistically-Based Warps
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
Statistical Computing on Manifolds: From Riemannian Geometry to Computational Anatomy
Emerging Trends in Visual Computing
Probabilistic models for shapes as continuous curves
Journal of Mathematical Imaging and Vision
On fiducial target registration error in the presence of anisotropic noise
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
Improved statistical TRE model when using a reference frame
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I
Bootstrap resampling for image registration uncertainty estimation without ground truth
IEEE Transactions on Image Processing
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
Image registration accuracy estimation without ground truth using bootstrap
CVAMIA'06 Proceedings of the Second ECCV international conference on Computer Vision Approaches to Medical Image Analysis
A comparison of shape matching methods for contour based pose estimation
IWCIA'06 Proceedings of the 11th international conference on Combinatorial Image Analysis
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In this paper, we propose and analyze several methods to estimate arigid transformation from a set of 3-D matched points or matchedframes, which are important features in geometric algorithms. Wealso develop tools to predict and verify the accuracy of theseestimations. The theoretical contributions are: an intrinsic model ofnoise for transformations based on composition rather than addition;a unified formalism for the estimation of both the rigidtransformation and its covariance matrix for points or framescorrespondences, and a statistical validation method to verify theerror estimation, which applies even when no “ground truth” isavailable. We analyze and demonstrate on synthetic data that ourscheme is well behaved. The practical contribution of the paper isthe validation of our transformation estimation method in the case of3-D medical images, which shows that an accuracy of the registrationfar below the size of a voxel can be achieved, and in the case ofprotein substructure matching, where frame features drasticallyimprove both selectivity and complexity.