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COMPGEOM
2011
ACM
14 years 1 months ago
Metric graph reconstruction from noisy data
Many real-world data sets can be viewed of as noisy samples of special types of metric spaces called metric graphs [16]. Building on the notions of correspondence and GromovHausdo...
Mridul Aanjaneya, Frédéric Chazal, D...
JGAA
2007
135views more  JGAA 2007»
14 years 9 months ago
Challenging Complexity of Maximum Common Subgraph Detection Algorithms: A Performance Analysis of Three Algorithms on a Wide Dat
Graphs are an extremely general and powerful data structure. In pattern recognition and computer vision, graphs are used to represent patterns to be recognized or classified. Det...
Donatello Conte, Pasquale Foggia, Mario Vento
COLT
2004
Springer
15 years 2 months ago
Regularization and Semi-supervised Learning on Large Graphs
We consider the problem of labeling a partially labeled graph. This setting may arise in a number of situations from survey sampling to information retrieval to pattern recognition...
Mikhail Belkin, Irina Matveeva, Partha Niyogi
CVPR
2009
IEEE
16 years 4 months ago
Unsupervised Learning for Graph Matching
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 learnin...
Marius Leordeanu, Martial Hebert
MM
2006
ACM
119views Multimedia» more  MM 2006»
15 years 3 months ago
Model generation for video-based object recognition
This paper presents a novel approach to object recognition involving a sparse 2D model and matching using video. The model is generated on the basis of geometry and image measurab...
Humera Noor, Shahid H. Mirza, Yaser Sheikh, Amit J...