Least-Squares Fitting of Two 3-D Point Sets
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Object modelling by registration of multiple range images
Image and Vision Computing - Special issue: range image understanding
Iterative point matching for registration of free-form curves and surfaces
International Journal of Computer Vision
Alignment by Maximization of Mutual Information
International Journal of Computer Vision
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Bundle Adjustment - A Modern Synthesis
ICCV '99 Proceedings of the International Workshop on Vision Algorithms: Theory and Practice
Surface registration by matching oriented points
NRC '97 Proceedings of the International Conference on Recent Advances in 3-D Digital Imaging and Modeling
Geometrical cloning of 3D objects via simultaneous registration of multiple range images
SMA '97 Proceedings of the 1997 International Conference on Shape Modeling and Applications (SMA '97)
Mutual Information Based Evaluation of 3D Building Models
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Five-Point Motion Estimation Made Easy
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Image Correlation for Shape, Motion and Deformation Measurements: Basic Concepts,Theory and Applications
Semi-variational registration of range images by non-rigid deformations
ACIVS'12 Proceedings of the 14th international conference on Advanced Concepts for Intelligent Vision Systems
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This paper presents a method for precise registration of 3D images acquired from a new sensor for 3D digitization moved manually by an operator around an object. The system is equipped with visual and inertial devices and with a speckle pattern projector. The presented method has been developed to address the problem that a moving speckle pattern during a sequence prevents from correlating points between images acquired from two successive viewpoints. So several solutions are proposed, based on images acquired with a moving speckle pattern. It improves ICP-based methods classically used for precise registration of two clouds of 3D points.