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» Coarse-to-Fine Object Recognition Using Shock Graphs
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ICPR
2002
IEEE
16 years 24 days ago
Relational Graph Labelling Using Learning Techniques and Markov Random Fields
This paper introduces an approach for handling complex labelling problems driven by local constraints. The purpose is illustrated by two applications: detection of the road networ...
Denis Rivière, Jean-Francois Mangin, Jean-M...
GBRPR
2005
Springer
15 years 5 months ago
Adaptive Pyramid and Semantic Graph: Knowledge Driven Segmentation
A method allowing to integrate syntactic and semantic approaches in an automatic segmentation process is described. This integration is possible thanks to the formalism of graphs....
Aline Deruyver, Yann Hodé, Eric Laemmer, Je...
SSPR
1998
Springer
15 years 3 months ago
Object Recognition from Large Structural Libraries
This paper presents a probabilistic similarity measure for object recognition from large libraries of line-patterns. We commence from a structural pattern representation which use...
Benoit Huet, Edwin R. Hancock
CVPR
2003
IEEE
16 years 1 months ago
Many-to-Many Graph Matching via Metric Embedding
Graph matching is an important component in many object recognition algorithms. Although most graph matching algorithms seek a one-to-one correspondence between nodes, it is often...
Yakov Keselman, Ali Shokoufandeh, M. Fatih Demirci...
PAMI
2010
260views more  PAMI 2010»
14 years 10 months ago
Unsupervised Object Segmentation with a Hybrid Graph Model (HGM)
—In this work, we address the problem of performing class-specific unsupervised object segmentation, i.e., automatic segmentation without annotated training images. Object segmen...
Guangcan Liu, Zhouchen Lin, Yong Yu, Xiaoou Tang