875 search results - page 22 / 175 » Linear Manifold Clustering |
121
Voted
IVC
2006
15 years 3 months ago
2006
We propose a novel approach for modeling, tracking and recognizing facial expressions. Our method works on a low dimensional expression manifold, which is obtained by Isomap embed...
176
Voted
NN
2002
Springer
15 years 3 months ago
2002
Springer
The self-organising map (SOM) has been successfully employed as a nonparametric method for dimensionality reduction and data visualisation. However, for visualisation the SOM requ...
137
Voted
AAAI
2007
15 years 6 months ago
2007
Recently the problem of dimensionality reduction has received a lot of interests in many fields of information processing. We consider the case where data is sampled from a low d...
150
Voted
CVPR
2007
IEEE
16 years 5 months ago
2007
IEEE
A good distance metric is crucial for unsupervised learning from high-dimensional data. To learn a metric without any constraint or class label information, most unsupervised metr...
123
Voted
ICML
2005
IEEE
16 years 4 months ago
2005
IEEE
Recently, several manifold learning algorithms have been proposed, such as ISOMAP (Tenenbaum et al., 2000), Locally Linear Embedding (Roweis & Saul, 2000), Laplacian Eigenmap ...