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» Mercer Kernels for Object Recognition with Local Features
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CVPR
2012
IEEE
13 years 6 months ago
RGB-(D) scene labeling: Features and algorithms
Scene labeling research has mostly focused on outdoor scenes, leaving the harder case of indoor scenes poorly understood. Microsoft Kinect dramatically changed the landscape, show...
Xiaofeng Ren, Liefeng Bo, Dieter Fox
137
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BVAI
2005
Springer
15 years 9 months ago
Learning Location Invariance for Object Recognition and Localization
A visual system not only needs to recognize a stimulus, it also needs to find the location of the stimulus. In this paper, we present a neural network model that is able to genera...
Gwendid T. van der Voort van der Kleij, Frank van ...
IBPRIA
2007
Springer
15 years 10 months ago
Unidimensional Multiscale Local Features for Object Detection Under Rotation and Mild Occlusions
Abstract. In this article, scale and orientation invariant object detection is performed by matching intensity level histograms. Unlike other global measurement methods, the presen...
Michael Villamizar, Alberto Sanfeliu, Juan Andrade...
CVPR
2007
IEEE
16 years 6 months ago
Flexible Object Models for Category-Level 3D Object Recognition
Today's category-level object recognition systems largely focus on fronto-parallel views of objects with characteristic texture patterns. To overcome these limitations, we pr...
Akash Kushal, Cordelia Schmid, Jean Ponce
MCS
2010
Springer
15 years 2 months ago
A Support Kernel Machine for Supervised Selective Combining of Diverse Pattern-Recognition Modalities
Abstract. The Support Kernel Machine (SKM) and the Relevance Kernel Machine (RKM) are two principles for selectively combining objectrepresentation modalities of different kinds b...
Alexander Tatarchuk, Eugene Urlov, Vadim Mottl, Da...