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» Image recognition using maximal cliques of interest points
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PAMI
2011
14 years 4 months ago
Learning Linear Discriminant Projections for Dimensionality Reduction of Image Descriptors
This paper proposes a general method for improving image descriptors using discriminant projections. Two methods based on Linear Discriminant Analysis have been recently introduce...
Hongping Cai, Krystian Mikolajczyk, Jiri Matas
ICPR
2006
IEEE
15 years 10 months ago
Monocular Vision Based SLAM for Mobile Robots
This paper describes a new vision based method for the Simultaneous Localization and Mapping of mobile robots. The only data used is a video input from a moving calibrated monocul...
E. Mouragnon, Fabien Dekeyser, Maxime Lhuillier, M...
ISVC
2010
Springer
14 years 8 months ago
How to Overcome Perceptual Aliasing in ASIFT?
SIFT is one of the most popular algorithms to extract points of interest from images. It is a scale+rotation invariant method. As a consequence, if one compares points of interest ...
Nicolas Noury, Frédéric Sur, Marie-O...
ICIAR
2010
Springer
15 years 2 months ago
Adaptation of SIFT Features for Robust Face Recognition
Abstract. The Scale Invariant Feature Transform (SIFT) is an algorithm used to detect and describe scale-, translation- and rotation-invariant local features in images. The origina...
Janez Krizaj, Vitomir Struc, Nikola Pavesic
FGR
2008
IEEE
180views Biometrics» more  FGR 2008»
15 years 4 months ago
Image-set matching using a geodesic distance and cohort normalization
An image-set based face recognition algorithm is proposed that exploits the full geometrical interpretation of Canonical Correlation Analysis (CCA). CCA maximizes the correlation ...
Yui Man Lui, J. Ross Beveridge, Bruce A. Draper, M...