Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
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
Using Prior Shapes in Geometric Active Contours in a Variational Framework
International Journal of Computer Vision
A Frequency Domain Technique for Range Data Registration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-scale EM-ICP: A Fast and Robust Approach for Surface Registration
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Non-rigid registration using distance functions
Computer Vision and Image Understanding - Special issue on nonrigid image registration
International Journal of Computer Vision
Shape Registration in Implicit Spaces Using Information Theory and Free Form Deformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
SGP '05 Proceedings of the third Eurographics symposium on Geometry processing
Laplace-Beltrami eigenfunctions for deformation invariant shape representation
SGP '07 Proceedings of the fifth Eurographics symposium on Geometry processing
Technical Section: Discrete Laplace-Beltrami operators for shape analysis and segmentation
Computers and Graphics
Laplace-Beltrami spectra as 'Shape-DNA' of surfaces and solids
Computer-Aided Design
Group-Wise Point-Set Registration Using a Novel CDF-Based Havrda-Charvát Divergence
International Journal of Computer Vision
International Journal of Computer Vision
Robust 3D object registration without explicit correspondence using geometric integration
Machine Vision and Applications - Integrated Imaging and Vision Techniques for Industrial Inspection
Robust rigid shape registration method using a level set formulation
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part II
Information-theoretic matching of two point sets
IEEE Transactions on Image Processing
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This paper proposes a novel similarity registration technique for volumetric shapes implicitly represented by characteristic functions (CFs). Here, the calculation of rotation parameters is considered as a spherical cross-correlation problem and the solution is therefore found using the standard phase correlation technique facilitated by principal components analysis (PCA). Thus, fast Fourier transform (FFT) is employed to vastly improve efficiency and robustness. Geometric moments are then used for shape scale estimation which is independent from rotation and translation parameters. It is numerically demonstrated that our registration method is able to handle shapes with various topologies and robust to noise and initial poses. Further validation of our method is performed by registering a lung database.