Curvature-based representation of objects from range data
Image and Vision Computing
Numerical grid generation: foundations and applications
Numerical grid generation: foundations and applications
Visual reconstruction
Constraints on deformable models: recovering 3D shape and nongrid motion
Artificial Intelligence
The Computation of Visible-Surface Representations
IEEE Transactions on Pattern Analysis and Machine Intelligence
One-Dimensional Regularization with Discontinuities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Inferring Surface Trace and Differential Structure from 3-D Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
On Three-Dimensional Surface Reconstruction Methods
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bayesian Modeling of Uncertainty in Low-Level Vision
Bayesian Modeling of Uncertainty in Low-Level Vision
Numerical Methods
Multiresolution stochastic hybrid shape models with fractal priors
ACM Transactions on Graphics (TOG) - Special issue on interactive sculpting
Shape Modeling with Front Propagation: A Level Set Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Mechanism of Automatic 3D Object Modeling
IEEE Transactions on Pattern Analysis and Machine Intelligence
General Object Reconstruction Based on Simplex Meshes
International Journal of Computer Vision
Elastically Adaptive Deformable Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Matching and Retrieval of Distorted and Occluded Shapes Using Dynamic Programming
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reconstructing a 3-D structure with multiple deformable solid primitives
Computers and Graphics
| Hi-index | 0.16 |
A technique for constructing a canonical surface parameterization in terms of lines of curvature is presented. Two methods of computing the canonical invariant representation are also presented. In the first method, a static instance of the controlled continuity spline is used for the stabilizer. Ways to modify it to reflect a change of parameters to the lines of curvature are described. In the second method, the dynamic instance of the controlled continuity spline called the deformable model is used. A force field defined in terms of the principal vectors is synthesized and applied to the parameter curves of the deformable model to coerce them along the lines of curvature. In essence, any transformation of parameters requires a modification of the stabilizer in the first method, whereas in the second method, it is tantamount to synthesizing a new force field. Experimental results with real and synthetic range data are included.