Exploiting multi-layer graph factorization for multi-attributed graph matching
نویسندگان
چکیده
منابع مشابه
Exploiting Multi-layer Graph Factorization for Multi-attributed Graph Matching
Multi-attributed graph matching is a problem of finding correspondences between two sets of data while considering their complex properties described in multiple attributes. However, the information of multiple attributes is likely to be oversimplified during a process that makes an integrated attribute, and this degrades the matching accuracy. For that reason, a multi-layer graph structure-bas...
متن کاملMulti-attributed Graph Matching with Multi-layer Random Walks
This paper addresses the multi-attributed graph matching problem considering multiple attributes jointly while preserving the characteristics of each attribute. Since most of conventional graph matching algorithms integrate multiple attributes to construct a single attribute in an oversimplified way, the information from multiple attributes are not often fully exploited. In order to solve this ...
متن کاملMulti-layer Random Walks Synchronization for Multi-attributed Multiple Graph Matching
Many applications in computer vision can be formulated as a multiple graph matching problem that finds global correspondences across a bunch of data. To solve this problem, matching consistency should be carefully considered with matching accuracy to prevent conflicts between graph pairs. In this paper, we aim to solve a multiple graph matching problem in complicated environments by using multi...
متن کاملMulti-Attributed Graph Matching: a Spectral Clustering Approach
We present a Multiple Attribute Graph (MARG) Matching algorithm. The algorithm operates on a strong product graph, where vertices correspond to hypothesized matchings between two nodes and edges specify compatibilities between two matches. We show how the matching problem reduces to partitioning the strong product graph, which we solve with spectral clustering. We test our algorithm on a few im...
متن کاملDistributable Consistent Multi-Graph Matching
In this paper we propose an optimization-based framework to multiple graph matching. The framework takes as input maps computed between pairs of graphs, and outputs maps that 1) are consistent among all pairs of graphs, and 2) preserve edge connectivity between pairs of graphs. We show how to formulate this as solving a piece-wise low-rank matrix recovery problem using a generalized message pas...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Pattern Recognition Letters
سال: 2019
ISSN: 0167-8655
DOI: 10.1016/j.patrec.2018.09.024