Hierarchical Chamfer Matching: A Parametric Edge Matching Algorithm
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
Zippered polygon meshes from range images
SIGGRAPH '94 Proceedings of the 21st annual conference on Computer graphics and interactive techniques
Statistical Approaches to Feature-Based Object Recognition
International Journal of Computer Vision
Simultaneous registration of multiple range views for use in reverse engineering of CAD models
Computer Vision and Image Understanding - Special issue on CAD-based computer vision
Robust Point Correspondence Applied to Two-and Three-Dimensional Image Registration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computational Framework for Segmentation and Grouping
Computational Framework for Segmentation and Grouping
Registration and integration of textured 3-D data
NRC '97 Proceedings of the International Conference on Recent Advances in 3-D Digital Imaging and Modeling
Robust Affine Motion Estimation in Joint Image Space Using Tensor Voting
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 4 - Volume 4
Extension of the ICP Algorithm to Non-Rigid Intensity-Based Registration of 3D Volumes
MMBIA '96 Proceedings of the 1996 Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA '96)
Registration of Multiple Point Sets
ICPR '96 Proceedings of the 13th International Conference on Pattern Recognition - Volume 2
Registration of 3D Points Using Geometric Algebra and Tensor Voting
International Journal of Computer Vision
The Use of Geometric Algebra for 3D Modeling and Registration of Medical Data
Journal of Mathematical Imaging and Vision
Fast parametric elastic image registration
IEEE Transactions on Image Processing
Image Morphing in Frequency Domain
Journal of Mathematical Imaging and Vision
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In this paper, we present a novel algorithm that combines the power of expression of Geometric Algebra with the robustness of Tensor Voting to find the correspondences between two sets of 2D points with an underlying rigid transformation. Unlike other popular algorithms for point registration (like the Iterated Closest Points), our algorithm does not require an initialization, works equally well with small and large transformations between the data sets, performs even in the presence of large amounts of outliers (90% and more), and have less chance to be trapped in "local minima". Furthermore, we will show how this algorithm can be easily extended to account for multiple overlapping motions and certain non-rigid transformations.