Results 1 - 10 of 519,112

A Graduated Assignment Algorithm for Graph Matching

by Steven Gold, Anand Rangarajan , 1996
"... A graduated assignment algorithm for graph matching is presented which is fast and accurate even in the presence of high noise. By combining graduated non-convexity, twoway (assignment) constraints, and sparsity, large improvements in accuracy and speed are achieved. Its low order computational comp ..."
Abstract - Cited by 373 (15 self) - Add to MetaCart
A graduated assignment algorithm for graph matching is presented which is fast and accurate even in the presence of high noise. By combining graduated non-convexity, twoway (assignment) constraints, and sparsity, large improvements in accuracy and speed are achieved. Its low order computational

Similarity Flooding: A Versatile Graph Matching Algorithm and Its Application to Schema Matching

by Sergey Melnik, Hector Garcia-molina, Erhard Rahm , 2002
"... Matching elements of two data schemas or two data instances plays a key role in data warehousing, e-business, or even biochemical applications. In this paper we present a matching algorithm based on a fixpoint computation that is usable across different scenarios. The algorithm takes two graphs (sch ..."
Abstract - Cited by 577 (12 self) - Add to MetaCart
Matching elements of two data schemas or two data instances plays a key role in data warehousing, e-business, or even biochemical applications. In this paper we present a matching algorithm based on a fixpoint computation that is usable across different scenarios. The algorithm takes two graphs

Balanced graph matching

by Timothee Cour, Praveen Srinivasan, Jianbo Shi - In NIPS , 2006
"... Graph matching is a fundamental problem in Computer Vision and Machine Learning. We present two contributions. First, we give a new spectral relaxation technique for approximate solutions to matching problems, that naturally incorporates one-to-one or one-to-many constraints within the relaxation sc ..."
Abstract - Cited by 89 (4 self) - Add to MetaCart
Graph matching is a fundamental problem in Computer Vision and Machine Learning. We present two contributions. First, we give a new spectral relaxation technique for approximate solutions to matching problems, that naturally incorporates one-to-one or one-to-many constraints within the relaxation

Face recognition by elastic bunch graph matching,

by Laurenz Wiskott , ‡ , Jean-Marc Fellous , § , Norbert Krüger , ¶ , Christoph Von Der Malsburg - IEEE Trans. Patt. Anal. Mach. Intell. , 1997
"... Abstract We present a system for recognizing human faces from single images out of a large database containing one image per person. The task is difficult because of image variation in terms of position, size, expression, and pose. The system collapses most of this variance by extracting concise fa ..."
Abstract - Cited by 344 (9 self) - Add to MetaCart
face descriptions in the form of image graphs. In these, fiducial points on the face (eyes, mouth, etc.) are described by sets of wavelet components (jets). Image graph extraction is based on a novel approach, the bunch graph, which is constructed from a small set of sample image graphs. Recognition

Learning Graph Matching

by Tibério S. Caetano, Li Cheng, Quoc V. Le, Alex J. Smola
"... 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 graphs and pattern recognition amounts to finding a correspondence between the nodes of different graphs. There are many way ..."
Abstract - Cited by 81 (9 self) - Add to MetaCart
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 graphs and pattern recognition amounts to finding a correspondence between the nodes of different graphs. There are many

THIRTY YEARS OF GRAPH MATCHING IN PATTERN RECOGNITION

by D. Conte , P. Foggia , C. Sansone, M. Vento , 2004
"... A recent paper posed the question: "Graph Matching: What are we really talking about?". Far from providing a definite answer to that question, in this paper we will try to characterize the role that graphs play within the Pattern Recognition field. To this aim two taxonomies are presented ..."
Abstract - Cited by 231 (1 self) - Add to MetaCart
A recent paper posed the question: "Graph Matching: What are we really talking about?". Far from providing a definite answer to that question, in this paper we will try to characterize the role that graphs play within the Pattern Recognition field. To this aim two taxonomies are presented

Factorized Graph Matching

by Feng Zhou, Fernando De la Torre
"... Graph matching plays a central role in solving correspondence problems in computer vision. Graph matching problems that incorporate pair-wise constraints can be cast as a quadratic assignment problem (QAP). Unfortunately, QAP is NP-hard and many algorithms have been proposed to solve different relax ..."
Abstract - Cited by 9 (0 self) - Add to MetaCart
Graph matching plays a central role in solving correspondence problems in computer vision. Graph matching problems that incorporate pair-wise constraints can be cast as a quadratic assignment problem (QAP). Unfortunately, QAP is NP-hard and many algorithms have been proposed to solve different

An Eigendecomposition Approach to Weighted Graph Matching Problems

by Shinji Umeyama , 1988
"... This paper discusses an approximate solution to the weighted graph matching prohlem (WGMP) for both undirected and directed graphs. The WGMP is the problem of f inding the optimum matching between two weighted graphs, which are graphs with weights at each arc. The proposed method employs an analytic ..."
Abstract - Cited by 202 (0 self) - Add to MetaCart
This paper discusses an approximate solution to the weighted graph matching prohlem (WGMP) for both undirected and directed graphs. The WGMP is the problem of f inding the optimum matching between two weighted graphs, which are graphs with weights at each arc. The proposed method employs

Unsupervised Learning for Graph Matching

by Marius Leordeanu, Martial Hebert - Computer Vision and Pattern Recognition
"... Graph matching is an important problem in computer vision. It is used in 2D and 3D object matching and recognition. Despite its importance, there is little literature on learning the parameters that control the graph matching problem, even though learning is important for improving the matching rate ..."
Abstract - Cited by 28 (3 self) - Add to MetaCart
Graph matching is an important problem in computer vision. It is used in 2D and 3D object matching and recognition. Despite its importance, there is little literature on learning the parameters that control the graph matching problem, even though learning is important for improving the matching

Seeded Graph Matching∗

by Donniell E. Fishkind, Sancar Adali, Carey E. Priebe , 2014
"... Graph inference is a burgeoning field in the applied and theoretical statistics communities, as well as throughout the wider world of science, engineering, business, etc. Given two graphs on the same number of vertices, the graph matching problem is to find a bijection between the two vertex sets wh ..."
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Graph inference is a burgeoning field in the applied and theoretical statistics communities, as well as throughout the wider world of science, engineering, business, etc. Given two graphs on the same number of vertices, the graph matching problem is to find a bijection between the two vertex sets
Results 1 - 10 of 519,112