Recognition of occluded objects: a cluster-structure algorithm
Pattern Recognition
An Efficiently Computable Metric for Comparing Polygonal Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognition of partially occluded objects using B-spline representation
Pattern Recognition
Statistical Approaches to Feature-Based Object Recognition
International Journal of Computer Vision
Matching Hierarchical Structures Using Association Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shock Graphs and Shape Matching
International Journal of Computer Vision
Structural Graph Matching Using the EM Algorithm and Singular Value Decomposition
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
Partially Occluded Object Recognition Using Statistical Models
International Journal of Computer Vision
Comparing Images Using the Hausdorff Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Graph-Spectral Approach to Correspondence Matching
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 4 - Volume 4
Shape Matching: Similarity Measures and Algorithms
SMI '01 Proceedings of the International Conference on Shape Modeling & Applications
Indexing pictorial documents by their content: a survey of current techniques
Image and Vision Computing
Recognizing multiple overlapping objects in image: an optimal formulation
IEEE Transactions on Image Processing
Dynamic learning from multiple examples for semantic object segmentation and search
Computer Vision and Image Understanding
ALSBIR: A local-structure-based image retrieval
Pattern Recognition
An elastic partial shape matching technique
Pattern Recognition
Detection and recognition of contour parts based on shape similarity
Pattern Recognition
Similarity Invariant Delaunay Graph Matching
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Shape recognition and retrieval: A structural approach using velocity function
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
Partial matching of garment panel shapes with dynamic sketching design
Proceedings of the 1st Augmented Human International Conference
Boundary fragment matching and articulated pose under occlusion
AMDO'06 Proceedings of the 4th international conference on Articulated Motion and Deformable Objects
Partial retrieval of CAD models based on the gradient flows in Lie group
Pattern Recognition
Pre-organizing Shape Instances for Landmark-Based Shape Correspondence
International Journal of Computer Vision
Shape parametrization and contour curvature using method of hurwitz-radon matrices
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part I
Partial retrieval of CAD models based on local surface region decomposition
Computer-Aided Design
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We propose a new partial shape recognition algorithm by sub-matrix matching using a proximity-based shape representation. Given one or more example object templates and a number of candidate object regions in an image, points with local maximum curvature along contours of each are chosen as feature points to compute distance matrices for each candidate object region and example template(s). A sub-matrix matching algorithm is then proposed to determine correspondences for evaluation of partial similarity between an example template and a candidate object region. The method is translation, rotation, scale and reflection invariant. Applications of the proposed partial matching technique include recognition of partially occluded objects in images as well as significant acceleration of recognition/matching of full (non-occluded) objects for object based image labeling by learning from examples. The speed up in the latter application comes from the fact that we can now search only those combinations of regions in the neighborhood of potential partial matches as soon as they are identified, as opposed to all combinations of regions as was done in our prior work [Xu et al., Object formation and retrieval using a learning-based hierarchical content-description, Proceedings of the ICIP, Kobe, Japan 1999]. Experimental results are provided to demonstrate both applications.