Multi-Level Shape Representation Using Global Deformations andLocally Adaptive Finite Elements
International Journal of Computer Vision
A Level-Set Approach to 3D Reconstruction from Range Data
International Journal of Computer Vision
Nonrigid Motion Analysis Based on Dynamic Refinement of Finite Element Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Maximum-Likelihood Surface Estimator for Dense Range Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonrigid Motion Analysis Based on Dynamic Refinement of Finite Element Models
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Higher-Order Nonlinear Priors for Surface Reconstruction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Surface Reconstruction of Noisy and Defective Data Sets
VIS '04 Proceedings of the conference on Visualization '04
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We propose a shape representation scheme which allows two shapes to be combined into a single model. The desired regions of the two shapes are selected, and then merged together forming a blended shape. For reconstruction, blending is incorporated into a deformable model framework. The model automatically adapts to the data, blending when necessary. Hierarchical blending allows multiple blends of a shape to occur forming an evolution from the initial shape of a sphere to the final shape. Blending also allows the insertion of a hole between arbitrary locations. The models used are globally defined, making the recovered shape a natural symbolic description. We present reconstruction experiments involving shapes of various topologies.