A Tensor-Based Algorithm for High-Order Graph Matching 论文

详细信息

发表期刊/会议

IEEE Transactions on Pattern Analysis and Machine Intelligence

发表日期

2011-06-17

发表年份

2011

摘要

This paper addresses the problem of establishing correspondences between two sets of visual features using higher order constraints instead of the unary or pairwise ones used in classical methods. Concretely, the corresponding hypergraph matching problem is formulated as the maximization of a multilinear objective function over all permutations of the features. This function is defined by a tensor representing the affinity between feature tuples. It is maximized using a generalization of spectral techniques where a relaxed problem is first solved by a multidimensional power method and the solution is then projected onto the closest assignment matrix. The proposed approach has been implemented, and it is compared to state-of-the-art algorithms on both synthetic and real data.