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» Using Component Features for Face Recognition
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CVPR
2008
IEEE
14 years 9 months ago
Where am I: Place instance and category recognition using spatial PACT
We introduce spatial PACT (Principal component Analysis of Census Transform histograms), a new representation for recognizing instances and categories of places or scenes. Both pl...
Jianxin Wu, James M. Rehg
ICPR
2000
IEEE
14 years 8 months ago
Image Recognition on the Neural Network Based on Multi-Valued Neurons
Multi-valued neurons are the neural processing elements with complex-valued weights, huge functionality (it is possible to implement on the single neuron arbitrary mapping describ...
Igor N. Aizenberg, Naum N. Aizenberg, Constantine ...
NECO
1998
151views more  NECO 1998»
13 years 7 months ago
Nonlinear Component Analysis as a Kernel Eigenvalue Problem
We describe a new method for performing a nonlinear form of Principal Component Analysis. By the use of integral operator kernel functions, we can e ciently compute principal comp...
Bernhard Schölkopf, Alex J. Smola, Klaus-Robe...
SMA
2008
ACM
173views Solid Modeling» more  SMA 2008»
13 years 7 months ago
Visibility-based feature extraction from discrete models
In this paper, we present a new visibility-based feature extraction algorithm from discrete models as dense point clouds resulting from laser scans. Based on the observation that ...
Antoni Chica
ECCV
2000
Springer
14 years 9 months ago
Unsupervised Learning of Models for Recognition
We present a method to learn object class models from unlabeled and unsegmented cluttered scenes for the purpose of visual object recognition. We focus on a particular type of mode...
Markus Weber, Max Welling, Pietro Perona