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» Mercer Kernels for Object Recognition with Local Features
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CVPR
2009
IEEE
16 years 11 months ago
Let the Kernel Figure it Out; Principled Learning of Pre-processing for Kernel Classifiers
Most modern computer vision systems for high-level tasks, such as image classification, object recognition and segmentation, are based on learning algorithms that are able to se...
Peter V. Gehler, Sebastian Nowozin
ICPR
2008
IEEE
15 years 10 months ago
Combining local descriptors for 3D object recognition and categorization
Various local descriptors have been used successfully in a variety of tasks including object recognition. Although different descriptors have been shown to have different strength...
Andrea Salgian
ICPR
2008
IEEE
16 years 5 months ago
Multiple kernel learning from sets of partially matching image features
Abstract: Kernel classifiers based on Support Vector Machines (SVM) have achieved state-ofthe-art results in several visual classification tasks, however, recent publications and d...
Guo ShengYang, Min Tan, Si-Yao Fu, Zeng-Guang Hou,...
BMVC
2001
15 years 6 months ago
Recognising Trajectories of Facial Identities Using Kernel Discriminant Analysis
We present a comprehensive approach to address three challenging problems in face recognition: modelling faces across multi-views, extracting the non-linear discriminating feature...
Yongmin Li, Shaogang Gong, Heather M. Liddell
CVPR
2010
IEEE
16 years 11 days ago
Multi-Class Object Localization by Combining Local Contextual Interactions
Recent work in object localization has shown that the use of contextual cues can greatly improve accuracy over models that use appearance features alone. Although many of these mo...
Carolina Galleguillos, Brian McFee, Gert Lanckriet