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» Mercer Kernels for Object Recognition with Local Features
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CVPR
2012
IEEE
13 years 6 months ago
Locality-constrained and spatially regularized coding for scene categorization
Improving coding and spatial pooling for bag-of-words based feature design have gained a lot of attention in recent works addressing object recognition and scene classification. ...
Aymen Shabou, Hervé Le Borgne
DICTA
2009
15 years 5 months ago
SIFTing the Relevant from the Irrelevant: Automatically Detecting Objects in Training Images
Many state-of-the-art object recognition systems rely on identifying the location of objects in images, in order to better learn its visual attributes. In this paper, we propose fo...
Edmond Zhang, Michael Mayo
ICIAR
2010
Springer
15 years 9 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
TNN
2008
128views more  TNN 2008»
15 years 4 months ago
Nonnegative Matrix Factorization in Polynomial Feature Space
Abstract--Plenty of methods have been proposed in order to discover latent variables (features) in data sets. Such approaches include the principal component analysis (PCA), indepe...
Ioan Buciu, Nikos Nikolaidis, Ioannis Pitas
TIP
2008
287views more  TIP 2008»
15 years 4 months ago
3-D Object Recognition Using 2-D Views
We consider the problem of recognizing 3-D objects from 2-D images using geometric models and assuming different viewing angles and positions. Our goal is to recognize and localize...
Wenjing Li, George Bebis, Nikolaos G. Bourbakis