Incorporating Discrete Constraints Into Random Walk-Based Graph Matching
Yang X(杨旭)
Graph matching is a fundamental problem in theoretical computer science and artificial intelligence, and lays the foundation for many computer vision and machine learning
tasks. Approximate algorithms are necessary for graph matching due to its NP-complete nature. Inspired by the usage in network-related tasks, random walk is generalized to graph matching as a type of approximate algorithm. However, it may be inappropriate for the previous random walk-based graph matching algorithms to utilize continuous techniques without considering the discrete property. In this paper, we propose a novel
random walk-based graph matching algorithm by incorporating both continuous and discrete constraints in the optimization process. Specifically, after interpreting graph matching by random walk, the continuous constraints are directly embedded in the random walk constraint in each iteration. Further, both the assignment matrix (vector) and the pairwise similarity measure between graphs are iteratively updated according the discrete
constraints, which automatically leads the continuous solution
to the discrete domain. Comparisons on both synthetic and
real-world data demonstrate the effectiveness of the proposed
KeywordGraph Matching
Document Type期刊论文
Recommended Citation
GB/T 7714
Yang X. Incorporating Discrete Constraints Into Random Walk-Based Graph Matching[J]. RANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2017(0):0.
APA Yang X.(2017).Incorporating Discrete Constraints Into Random Walk-Based Graph Matching.RANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS(0),0.
MLA Yang X."Incorporating Discrete Constraints Into Random Walk-Based Graph Matching".RANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS .0(2017):0.
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