FORMS: a flexible object recognition and modeling system
International Journal of Computer Vision
Extraction of shape skeletons from grayscale images
Computer Vision and Image Understanding
Matching Hierarchical Structures Using Association Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shock Graphs and Shape Matching
International Journal of Computer Vision
Ligature instabilities in the perceptual organization of shape
Computer Vision and Image Understanding
Matching and Embedding through Edit-Union of Trees
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Many-to-many Matching of Attributed Trees Using Association Graphs and Game Dynamics
IWVF-4 Proceedings of the 4th International Workshop on Visual Form
A shock grammar for recognition
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Representation and Self-Similarity of Shapes
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
A skeletal measure of 2D shape similarity
Computer Vision and Image Understanding
An Axis-Based Representation for Recognition
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Skeleton Pruning by Contour Partitioning with Discrete Curve Evolution
IEEE Transactions on Pattern Analysis and Machine Intelligence
Indexing through laplacian spectra
Computer Vision and Image Understanding
Path Similarity Skeleton Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dissimilarity between two skeletal trees in a context
Pattern Recognition
Disconnected Skeleton: Shape at Its Absolute Scale
IEEE Transactions on Pattern Analysis and Machine Intelligence
Skeletal Shape Abstraction from Examples
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Disconnected skeleton [1] is a very coarse yet a very stable skeleton-based representation scheme for generic shape recognition in which recognition is performed mainly based on the structure of disconnection points of extracted branches, without explicitly using information about boundary details [2,3]. However, sometimes sensitivity to boundary details may be required in order to achieve the goal of recognition. In this study, we first present a simple way to enrich disconnected skeletons with radius functions. Next, we attempt to resolve the conflicting goals of stability and sensitivity by proposing a coarse-to-fine shape matching algorithm. As the first step, two shapes are matched based on the structure of their disconnected skeletons, and following to that, the computed matching cost is re-evaluated by taking into account the similarity of boundary details in the light of class-specific boundary deformations which are learned from a given set of examples.