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» Robot Localization Using a Computer Vision Sextant
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112
Voted
ICPR
2006
IEEE
16 years 3 months ago
Background Robust Object Labeling by Voting of Weight-Aggregated Local Features
In this paper, we present a new voting-based object labeling method that is robust to background clutter. The conventional simple voting method shows very poor performance under c...
In-So Kweon, Kuk-Jin Yoon, Sungho Kim
139
Voted
ICCV
2011
IEEE
14 years 2 months ago
Localized Principal Component Analysis based Curve Evolution: A Divide and Conquer Approach
We propose a novel localized principal component analysis (PCA) based curve evolution approach which evolves the segmenting curve semi-locally within various target regions (divis...
Vikram Appia, Balaji Ganapathy, Tracy Faber, Antho...
ICPR
2010
IEEE
15 years 2 months ago
A Discrete Labelling Approach to Attributed Graph Matching Using SIFT Features
Local invariant feature extraction methods are widely used for image-features matching. There exist a number of approaches aimed at the refinement of the matches between image-fe...
Gerard Sanromà, René Alquézar...
ICPR
2004
IEEE
16 years 3 months ago
Support Vector Machine with Local Summation Kernel for Robust Face Recognition
This paper presents Support Vector Machine (SVM) with local summation kernel for robust face recognition. In recent years, the effectiveness of SVM and local features is reported....
Kazuhiro Hotta
ICPR
2008
IEEE
15 years 9 months ago
Flexible object recognition in cluttered scenes using relative point distribution models
This paper introduces an edge-based object recognition method that is robust with respect to clutter, occlusion and object deformations. The method combines the use of local featu...
Alexandros Bouganis, Murray Shanahan