Retrieval of objects in video by similarity based on graph matching
Pattern Recognition Letters
Neural disparity computation for dense two-frame stereo correspondence
Pattern Recognition Letters
A differential geometric approach to representing the human actions
Computer Vision and Image Understanding
Shape modeling and matching in identifying 3D protein structures
Computer-Aided Design
Soft constraint abstraction based on semiring homomorphism
Theoretical Computer Science
A 3-D recognition and positioning algorithm using geometrical matching between primitive surfaces
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 2
Recognition and beautification of multi-stroke symbols in digital ink
Computers and Graphics
Indexing pictorial documents by their content: a survey of current techniques
Image and Vision Computing
Clustering graphs for visualization via node similarities
Journal of Visual Languages and Computing
Efficient many-to-many feature matching under the l1 norm
Computer Vision and Image Understanding
Structure and attribute index for approximate graph matching in large graphs
Information Systems
BPEL processes matchmaking for service discovery
ODBASE'06/OTM'06 Proceedings of the 2006 Confederated international conference on On the Move to Meaningful Internet Systems: CoopIS, DOA, GADA, and ODBASE - Volume Part I
Inexact graph matching for structural pattern recognition
Pattern Recognition Letters
Attributed graph similarity from the quantum jensen-shannon divergence
SIMBAD'13 Proceedings of the Second international conference on Similarity-Based Pattern Recognition
Textual and Content-Based Search in Repositories of Web Application Models
ACM Transactions on the Web (TWEB)
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In this paper we formally define the structural description of an object and the concepts of exact and inexact matching of two structural descriptions. We discuss the problems associated with a brute-force backtracking tree search for inexact matching and develop several different algorithms to make the tree search more efficient. We develop the formula for the expected number of nodes in the tree for backtracking alone and with a forward checking algorithm. Finally, we present experimental results showing that forward checking is the most efficient of the algorithms tested.