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» Position Estimation Using Principal Components of Range Data
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ICRA
1998
IEEE
148views Robotics» more  ICRA 1998»
13 years 8 months ago
Position Estimation Using Principal Components of Range Data
1 sensors is to construct a structural description from sensor data and to match this description to a previously acquired model [Crowley 85]. An alternative is to project individu...
James L. Crowley, Frank Wallner, Bernt Schiele
CSDA
2006
304views more  CSDA 2006»
13 years 4 months ago
Using principal components for estimating logistic regression with high-dimensional multicollinear data
The logistic regression model is used to predict a binary response variable in terms of a set of explicative ones. The estimation of the model parameters is not too accurate and t...
Ana M. Aguilera, Manuel Escabias, Mariano J. Valde...
SMI
2006
IEEE
144views Image Analysis» more  SMI 2006»
13 years 10 months ago
Robust Alignment of Multi-view Range Data to CAD Model
Surface matching is a common task in computer graphics and computer vision. In this paper, we introduce a novel algorithm that aligns scanned point-based surfaces to the related 3...
Xinju Li, Igor Guskov, Jacob Barhak
ICASSP
2010
IEEE
13 years 4 months ago
Direct importance estimation with probabilistic principal component analyzers
The importance estimation problem (estimating the ratio of two probability density functions) has recently gathered a great deal of attention for use in various applications, e.g....
Makoto Yamada, Masashi Sugiyama, Gordon Wichern
IEICET
2010
132views more  IEICET 2010»
13 years 3 months ago
Direct Importance Estimation with a Mixture of Probabilistic Principal Component Analyzers
Estimating the ratio of two probability density functions (a.k.a. the importance) has recently gathered a great deal of attention since importance estimators can be used for solvi...
Makoto Yamada, Masashi Sugiyama, Gordon Wichern, J...