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research article

Geometric Graph Matching Using Monte Carlo Tree Search

Pinheiro, Miguel Amavel
•
Kybic, Jan  
•
Fua, Pascal  
2017
Transactions on Pattern Analysis and Machine Intelligence (PAMI)

We present an efficient matching method for generalized geometric graphs. Such graphs consist of vertices in space connected by curves and can represent many real world structures such as road networks in remote sensing, or vessel networks in medical imaging. Graph matching can be used for very fast and possibly multimodal registration of images of these structures. We formulate the matching problem as a single player game solved using Monte Carlo Tree Search, which automatically balances exploring new possible matches and extending existing matches. Our method can handle partial matches, topological differences, geometrical distortion, does not use appearance information and does not require an initial alignment. Moreover, our method is very efficient-it can match graphs with thousands of nodes, which is an order of magnitude better than the best competing method, and the matching only takes a few seconds.

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Type
research article
DOI
10.1109/Tpami.2016.2636200
Web of Science ID

WOS:000412028600005

Author(s)
Pinheiro, Miguel Amavel
Kybic, Jan  
Fua, Pascal  
Date Issued

2017

Publisher

Ieee Computer Soc

Published in
Transactions on Pattern Analysis and Machine Intelligence (PAMI)
Volume

39

Issue

11

Start page

2171

End page

2185

Subjects

Geometric graph matching

•

Monte Carlo tree search

•

image registration

•

curve descriptor

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
CVLAB  
Available on Infoscience
November 8, 2017
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/141951
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