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» Learning the Kernel Combination for Object Categorization
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IJCV
2008
223views more  IJCV 2008»
13 years 7 months ago
Robust Object Detection with Interleaved Categorization and Segmentation
This paper presents a novel method for detecting and localizing objects of a visual category in cluttered real-world scenes. Our approach considers object categorization and figure...
Bastian Leibe, Ales Leonardis, Bernt Schiele
ICMLC
2010
Springer
13 years 6 months ago
Multiple kernel learning and feature space denoising
We review a multiple kernel learning (MKL) technique called p regularised multiple kernel Fisher discriminant analysis (MK-FDA), and investigate the effect of feature space denois...
Fei Yan, Josef Kittler, Krystian Mikolajczyk
PAMI
2012
11 years 10 months ago
Unsupervised Learning of Categorical Segments in Image Collections
Which one comes first: segmentation or recognition? We propose a unified framework for carrying out the two simultaneously and without supervision. The framework combines a fle...
Marco Andreetto, Lihi Zelnik-Manor, Pietro Perona
ICCV
2009
IEEE
1419views Computer Vision» more  ICCV 2009»
15 years 18 days ago
On Feature Combination for Multiclass Object Classification
A key ingredient in the design of visual object classification systems is the identification of relevant class specific aspects while being robust to intra-class variations. Whil...
Peter Gehler, Sebastian Nowozin
DAGM
2008
Springer
13 years 9 months ago
A Multiple Kernel Learning Approach to Joint Multi-class Object Detection
Most current methods for multi-class object classification and localization work as independent 1-vs-rest classifiers. They decide whether and where an object is visible in an imag...
Christoph H. Lampert, Matthew B. Blaschko