IEEE Transactions on Pattern Analysis and Machine Intelligence
An object centered hierarchical representation for 3D objects: the prism tree
Computer Vision, Graphics, and Image Processing
Hierarchical Shape Description Via the Multiresolution Symmetric Axis Transform
IEEE Transactions on Pattern Analysis and Machine Intelligence
Trace Inference, Curvature Consistency, and Curve Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Introduction to algorithms
Closed-Form Solutions for Physically Based Shape Modeling and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Simulating the Grassfire Transform Using an Active Contour Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parts of Visual Form: Computational Aspects
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Measurement of Visual Motion
Perception of 3-D Surfaces from 2-D Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
Comparing Images Using the Hausdorff Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Modal Matching for Correspondence and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Matching Hierarchical Structures Using Association Graphs
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Measures for Silhouettes Resemblance and Representative Silhouettes of Curved Objects
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
A shock grammar for recognition
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
FORMS: a flexible object recognition and modelling system
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Representation and Self-Similarity of Shapes
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Local Symmetries of Shapes in Arbitrary Dimension
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Shock Graphs and Shape Matching
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Affine Invariant Medial Axis and Skew Symmetry
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Representation and Detection of Deformable Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Matching Shape Sequences in Video with Applications in Human Movement Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
ALSBIR: A local-structure-based image retrieval
Pattern Recognition
Knowledge-based part correspondence
Pattern Recognition
Analysis of Two-Dimensional Non-Rigid Shapes
International Journal of Computer Vision
Strategies for shape matching using skeletons
Computer Vision and Image Understanding
Symmetry of Shapes Via Self-similarity
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II
Partial Similarity of Objects, or How to Compare a Centaur to a Horse
International Journal of Computer Vision
Journal of Visual Communication and Image Representation
Statistical Methods and Models for Video-Based Tracking, Modeling, and Recognition
Foundations and Trends in Signal Processing
Continuous curve matching with scale-space curvature and extrema-based scale selection
Scale Space'03 Proceedings of the 4th international conference on Scale space methods in computer vision
Shape evolution driven by a perceptually motivated measure
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
Shape classification based on skeleton path similarity
EMMCVPR'07 Proceedings of the 6th international conference on Energy minimization methods in computer vision and pattern recognition
A similarity-based approach for shape classification using Aslan skeletons
Pattern Recognition Letters
Skeleton-based segmentation and decomposition of raster pairs of shapes
Pattern Recognition and Image Analysis
Shape matching using coarse descriptors
International Journal of Computational Vision and Robotics
Image skeletonization based on curve skeleton extraction
HCII'11 Proceedings of the 14th international conference on Human-computer interaction: design and development approaches - Volume Part I
Measuring terrain distances through extracted channel networks
SIGSPATIAL Special
Strategies for part-based shape analysis using skeletons
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part I
Skeleton graph matching based on critical points using path similarity
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part III
Matching noisy outline contours using a descriptor reduction approach
ICISP'12 Proceedings of the 5th international conference on Image and Signal Processing
Shape Codification Indexing and Retrieval Using the Quad-Tree Structure
International Journal of Computer Vision and Image Processing
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Representing shapes in a compact and informative form is a significant problem for vision systems that must recognize or classify objects. We describe a compact representation model for two-dimensional (2D) shapes by investigating their self-similarities and constructing their shape axis trees (SA-trees). Our approach can be formulated as a variational one (or, equivalently, as MAP estimation of a Markov random field). We start with a 2D shape, its boundary contour, and two different parameterizations for the contour (one parameterization is oriented counterclockwise and the other clockwise). To measure its self-similarity, the two parameterizations are matched to derive the best set of one-to-one point-to-point correspondences along the contour. The cost functional used in the matching may vary and is determined by the adopted self-similarity criteria, e.g., cocircularity, distance variation, parallelism, and region homogeneity. The loci of middle points of the pairing contour points yield the shape axis and they can be grouped into a unique free tree structure, the SA-tree. By implicitly encoding the (local and global) shape information into an SA-tree, a variety of vision tasks, e.g., shape recognition, comparison, and retrieval, can be performed in a more robust and efficient way via various tree-based algorithms. A dynamic programming algorithm gives the optimal solution in O(N^4), where N is the size of the contour.