Abstract. Graph matching is often used for image recognition. Different kinds of graph matchings have been proposed such as (sub)graph isomorphism or error-tolerant graph matching...
As a fundamental problem in pattern recognition, graph matching has found a variety of applications in the field of computer vision. In graph matching, patterns are modeled as gr...
Abstract. Graph pattern matching is a central application in many fields. In various areas, the structure of the pattern can only be approximated and exact matching is then too ac...
Marwan Torki is a Ph. D. student in computer science department at Rutgers University. He took his M.Sc. and B.Sc. in computer science from department of computer science, faculty ...
We present an algorithm for graph matching in a pattern recognition context. This algorithm deals with weighted graphs, based on new structural and topological node signatures. Usi...
We propose a novel stochastic graph matching algorithm based on data-driven Markov Chain Monte Carlo (DDMCMC) sampling technique. The algorithm explores the solution space efficien...
Graph matching is a classical problem in pattern recognition with many applications, particularly when the graphs are embedded in Euclidean spaces, as is often the case for comput...
Julian McAuley, Teofilo de Campos, Tiberio Caetano
This paper exploits the properties of the commute time for the purposes of graph matching. Our starting point is the random walk on the graph, which is determined by the heat-kern...
Many vision tasks are posed as either graph partitioning (coloring) or graph matching (correspondence) problems. The former include segmentation and grouping, and the latter inclu...
Weighted graph matching is a good way to align a pair of shapes represented by a set of descriptive local features; the set of correspondences produced by the minimum cost matchin...