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» Graph-Theoretical Methods in Computer Vision
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CVPR
2012
IEEE
13 years 2 months ago
Complex loss optimization via dual decomposition
We describe a novel max-margin parameter learning approach for structured prediction problems under certain non-decomposable performance measures. Structured prediction is a commo...
Mani Ranjbar, Arash Vahdat, Greg Mori

Presentation
4053views
16 years 11 months ago
Graph Cuts vs. Level Sets
A nice presentation by Yuri Boykov, Daniel Cremers, Vladimir Kolmogorov, at the European Conference on Computer Vision (ECCV) 2006, that finds the relation between Graph Cuts and L...
Yuri Boykov, Daniel Cremers, Vladimir Kolmogorov
82
Voted
ICARCV
2002
IEEE
141views Robotics» more  ICARCV 2002»
15 years 5 months ago
An efficient binary corner detector
Corner extraction is an important task in many computer vision systems. The quality of the corners and the efficiency of the detection method are two very important aspects that ...
Parvanesh Saeedi, David Lowe, Peter Lawrence
ICPR
2004
IEEE
16 years 1 months ago
Action and Simultaneous Multiple-Person Identification Using Cubic Higher-Order Local Auto-Correlation
We propose a new method ? Cubic Higher-order Local Auto-Correlation (CHLAC) ? to address three-way data analysis. This method is a natural extension of Higherorder Local Auto-Corr...
Nobuyuki Otsu, Takumi Kobayashi
107
Voted
ICPR
2002
IEEE
16 years 1 months ago
Solving the Small Sample Size Problem of LDA
The small sample size problem is often encountered in pattern recognition. It results in the singularity of the within-class scatter matrix Sw in Linear Discriminant Analysis (LDA...
Rui Huang, Qingshan Liu, Hanqing Lu, Songde Ma