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» Mercer Kernels for Object Recognition with Local Features
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CVPR
2007
IEEE
16 years 5 months ago
Robust Local Features and their Application in Self-Calibration and Object Recognition on Embedded Systems
In recent years many powerful Computer Vision algorithms have been invented, making automatic or semiautomatic solutions to many popular vision tasks, such as visual object recogn...
Clemens Arth, Christian Leistner, Horst Bischof
108
Voted
ICPR
2008
IEEE
16 years 5 months ago
Local shape features for object recognition
We present a shape matching algorithm based on the chamfer distance transform which can be easily integrated into the well-known SIFT framework. The shape matching was designed to...
Bernd Heisele, Carlos Rocha
124
Voted
CVPR
2008
IEEE
16 years 5 months ago
Relaxed matching kernels for robust image comparison
The popular bag-of-features representation for object recognition collects signatures of local image patches and discards spatial information. Some have recently attempted to at l...
Andrea Vedaldi, Stefano Soatto
136
Voted
ECCV
2010
Springer
15 years 9 months ago
3D Point Correspondence by Minimum Description Length in Feature Space
Abstract. Finding point correspondences plays an important role in automatically building statistical shape models from a training set of 3D surfaces. For the point correspondence ...
152
Voted
TIP
2011
217views more  TIP 2011»
14 years 10 months ago
Contextual Object Localization With Multiple Kernel Nearest Neighbor
—Recently, many object localization models have shown that incorporating contextual cues can greatly improve accuracy over using appearance features alone. Therefore, many of the...
Brian McFee, Carolina Galleguillos, Gert R. G. Lan...