Biological Cybernetics
Computer Vision, Graphics, and Image Processing
Height and gradient from shading
International Journal of Computer Vision
Hands: a pattern theoretic study of biological shapes
Hands: a pattern theoretic study of biological shapes
An Efficiently Computable Metric for Comparing Polygonal Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence
A contour-oriented approach to shape analysis
A contour-oriented approach to shape analysis
A survey of moment-based techniques for unoccluded object representation and recognition
CVGIP: Graphical Models and Image Processing
Metamorphosis of Arbitrary Triangular Meshes
IEEE Computer Graphics and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Tracking Points on Deformable Objects Using Curvature Information
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Curves Matching Using Geodesic Paths
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
MMBIA '00 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis
Shape Matching: Similarity Measures and Algorithms
SMI '01 Proceedings of the International Conference on Shape Modeling & Applications
Statistical shape modeling using MDL incorporating shape, appearance, and expert knowledge
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I
3D anatomical shape atlas construction using mesh quality preserved deformable models
Computer Vision and Image Understanding
| Hi-index | 0.00 |
We present a learning method that introduces explicit knowledge into the shape correspondence problem. Given two input curves to be matched, our approach establishes a dense correspondence field between them, where the characteristics of the matching field closely resemble those in an a priori learning set. We build a shape distance matrix from the values of a shape descriptor computed at every point along the curves. This matrix embeds the correspondence problem in a highly expressive and redundant construct and provides the basis for a pattern matching strategy for curve matching. We selected the previously introduced observed transport measure as a shape descriptor, as its properties make it particularly amenable to the matching problem. Synthetic and real examples are presented along with discussions of the robustness and applications of the technique.