Matching Hierarchical Structures Using Association Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Local Form and Transitions of Symmetry Sets, Medial Axes, and Shocks
International Journal of Computer Vision - Special Issue on Computational Vision at Brown University
A shock grammar for recognition
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Recognition of Shapes by Editing Their Shock Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence
Transitions of the Pre-Symmetry Set
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Curves vs. skeletons in object recognition
Signal Processing - Special section on content-based image and video retrieval
Deriving the Medial Axis with geometrical arguments for planar shapes
Pattern Recognition Letters
Contour Grouping Based on Contour-Skeleton Duality
International Journal of Computer Vision
Computationally efficient matching of microRNA shapes using mutual symmetry
SIP '07 Proceedings of the Ninth IASTED International Conference on Signal and Image Processing
Efficient partial shape matching of outer contours
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part I
Circular Cone: A novel approach for protein ligand shape matching using modified PCA
Computer Methods and Programs in Biomedicine
On the Local Form and Transitions of Pre-symmetry Sets
Journal of Mathematical Imaging and Vision
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A novel shape descriptor is introduced. It groups pairs of points that share a geometrical property that is based on their mutual symmetry. The descriptor is visualized as a diagonally symmetric diagram with binary valued regions. This diagram is a fingerprint of global symmetry between pairs of points along the shape. The descriptive power of the method is tested on a well-known shape data base containing several classes of shapes and partially occluded shapes. First tests with simple, elementary matching algorithms show good results.