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» Mercer Kernels for Object Recognition with Local Features
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2861
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CVPR
2011
IEEE
1473views Computer Vision» more  CVPR 2011»
14 years 12 months ago
Object Recognition with Hierarchical Kernel Descriptors
Kernel descriptors provide a unified way to generate rich visual feature sets by turning pixel attributes into patch-level features, and yield impressive results on many object rec...
Liefeng Bo, Kevin Lai, Xiaofeng Ren and Dieter Fox
168
Voted
ICASSP
2011
IEEE
14 years 7 months ago
Generic object recognition using automatic region extraction and dimensional feature integration utilizing multiple kernel learn
Recently, in generic object recognition research, a classification technique based on integration of image features is garnering much attention. However, with a classifying techn...
Toru Nakashika, Akira Suga, Tetsuya Takiguchi, Yas...
134
Voted
CVPR
2004
IEEE
16 years 5 months ago
Shaping Receptive Fields for Affine Invariance
The Gaussian kernel has played a central role in multi-scale methods for feature extraction and matching. In this paper, a method for shaping the filter using the local image stru...
S. Ravela
CVPR
2001
IEEE
16 years 5 months ago
3D Object Recognition from Range Images using Local Feature Histograms
This paper explores a view-based approach to recognize free-form objects in range images. We are using a set of local features that are easy to calculate and robust to partial occ...
Bastian Leibe, Bernt Schiele, Günter Hetzel, ...
ICIP
2005
IEEE
15 years 9 months ago
View independent face recognition based on kernel principal component analysis of local parts
This paper presents a view independent face recognition method based on kernel principal component analysis (KPCA) of local parts. View changes induce large variation in feature s...
Koji Hotta