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» Surface Reconstruction using Learned Shape Models
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ICCV
2007
IEEE
14 years 11 months ago
Spherical-Homoscedastic Shapes
Shape analysis requires invariance under translation, scale and rotation. Translation and scale invariance can be realized by normalizing shape vectors with respect to their mean ...
Onur C. Hamsici, Aleix M. Martínez
AIED
2007
Springer
14 years 3 months ago
Comparing Linguistic Features for Modeling Learning in Computer Tutoring
We compare the relative utility of different automatically computable linguistic feature sets for modeling student learning in computer dialogue tutoring. We use the PARADISE frame...
Katherine Forbes-Riley, Diane J. Litman, Amruta Pu...
ICIP
2006
IEEE
14 years 10 months ago
A Probabilistic Approach to Robust Shape Matching
We present a probabilistic approach to shape matching which is invariant to rotation, translation and scaling. Shapes are represented by unlabeled point sets, so discontinuous bou...
Graham McNeill, Sethu Vijayakumar
GMP
2006
IEEE
121views Solid Modeling» more  GMP 2006»
14 years 3 months ago
Preserving Form-Features in Interactive Mesh Deformation
Interactive mesh editing techniques that preserve discrete differential properties are promising to support the design of mechanical parts such as automobile sheet metal panels. H...
Hiroshi Masuda, Yasuhiro Yoshioka, Yoshiyuki Furuk...
CVPR
1997
IEEE
14 years 1 months ago
Learning bilinear models for two-factor problems in vision
In many vision problems, we want to infer two (or more) hidden factors which interact to produce our observations. We may want to disentangle illuminant and object colors in color...
William T. Freeman, Joshua B. Tenenbaum