Three-dimensional object recognition from single two-dimensional images
Artificial Intelligence
Classification of Partial 2-D Shapes Using Fourier Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Contour sequence moments for the classification of closed planar shapes
Pattern Recognition
Invariant Image Recognition by Zernike Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
A retrieval technique for similar shapes
SIGMOD '91 Proceedings of the 1991 ACM SIGMOD international conference on Management of data
International Journal of Computer Vision
Object recognition based on moment (or algebraic) invariants
Geometric invariance in computer vision
Local Invariants For Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual learning and recognition of 3-D objects from appearance
International Journal of Computer Vision
Fast multiresolution image querying
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Matching Using Deformable Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using Discriminant Eigenfeatures for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
FORMS: a flexible object recognition and modeling system
International Journal of Computer Vision
A Graduated Assignment Algorithm for Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual Image Retrieval by Elastic Matching of User Sketches
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computable elastic distances between shapes
SIAM Journal on Applied Mathematics
Matching Hierarchical Structures Using Association Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shock Graphs and Shape Matching
International Journal of Computer Vision
A tree-edit-distance algorithm for comparing simple, closed shapes
SODA '00 Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms
Shape matching using edit-distance: an implementation
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
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
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generic Shape Learning and Recognition
ECCV '96 Proceedings of the International Workshop on Object Representation in Computer Vision II
Shock-Based Indexing into Large Shape Databases
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
CBAIVL '00 Proceedings of the IEEE Workshop on Content-based Access of Image and Video Libraries (CBAIVL'00)
Model-Based Object Recognition - A Survey of Recent Research
Model-Based Object Recognition - A Survey of Recent Research
A Similarity-Based Aspect-Graph Approach to 3D Object Recognition
International Journal of Computer Vision
Shape retrieval based on dynamic programming
IEEE Transactions on Image Processing
Characterizing the dynamics of symmetry breaking in genetic programming
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Shape representation by a network of V4-like cells
Neural Networks
Kernel PCA for similarity invariant shape recognition
Neurocomputing
Content-based image retrieval methods
Programming and Computing Software
The VLDB Journal — The International Journal on Very Large Data Bases
A new method for the positioning and matching of shape outlines
AIKED'09 Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases
Shape matching by curve modelling and alignment
WSEAS Transactions on Information Science and Applications
A Graph-Based Approach for Shape Skeleton Analysis
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
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
Shape geodesics for boundary-based object recognition and retrieval
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Variational shape matching for shape classification and retrieval
Pattern Recognition Letters
Monte carlo evaluation of the hausdorff distance for shape matching
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
Describing and matching 2d shapes by their points of mutual symmetry
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
On the Local Form and Transitions of Pre-symmetry Sets
Journal of Mathematical Imaging and Vision
Hi-index | 0.00 |
The type of representation used in describing shape can have a significant impact on the effectiveness and efficiency of a recognition strategy. Shape has been represented by a point set, outline curve and shock-graph (medial axis). The curve-based representation can be viewed as point-based representation with additional organization, namely, order along a contour; shock-based representation, in turn, Can be viewed as curve-based representation with additional organization, namely, pairing of contours. This additional complexity in organization leads to greater computational effort in deriving and matching these representations. However, it leads to an increase in robustness in the presence of variations. In This paper, we examine the tradeoff between robustness and computational complexity for curve-and shock-based representations. Our results indicate that the additional computational effort required in shock-graph matching is worthwhile in the presence of large amount variations, in particular those involving the presence of articulation or rearrangement of parts. However, when the space of variations is smaller, curve matching is a better strategy due to its lower complexity and roughly equivalent recognition rate.