123 search results - page 9 / 25 » Nonrigid Embeddings for Dimensionality Reduction |
IJON
2010
13 years 5 months ago
2010
Graph construction plays a key role on learning algorithms based on graph Laplacian. However, the traditional graph construction approaches of -neighborhood and k-nearest-neighbor...
ICIP
2010
IEEE
13 years 5 months ago
2010
IEEE
Many classes of image data span a low dimensional nonlinear space embedded in the natural high dimensional image space. We adopt and generalize a recently proposed dimensionality ...
ICCV
2007
IEEE
14 years 9 months ago
2007
IEEE
Invariant feature descriptors such as SIFT and GLOH have been demonstrated to be very robust for image matching and visual recognition. However, such descriptors are generally par...
IBPRIA
2003
Springer
14 years 28 days ago
2003
Springer
The dimensionality of the input data often far exceeds their intrinsic dimensionality. As a result, it may be difficult to recognize multidimensional data, especially if the number...
BMVC
2010
13 years 5 months ago
2010
We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...