12 search results - page 2 / 3 » Neighborhood denoising for learning high-dimensional graspin... |
AMDO
2006
Springer
13 years 11 months ago
2006
Springer
Abstract. We propose motion manifold learning and motion primitive segmentation framework for human motion synthesis from motion-captured data. High dimensional motion capture date...
ICCV
2005
IEEE
14 years 9 months ago
2005
IEEE
Recently there has been a lot of interest in geometrically motivated approaches to data analysis in high dimensional spaces. We consider the case where data is drawn from sampling...
ICIP
2010
IEEE
13 years 5 months ago
2010
IEEE
Discovering local geometry of low-dimensional manifold embedded into a high-dimensional space has been widely studied in the literature of machine learning. Counter-intuitively, w...
CVPR
2006
IEEE
14 years 9 months ago
2006
IEEE
Dimensionality reduction involves mapping a set of high dimensional input points onto a low dimensional manifold so that "similar" points in input space are mapped to ne...
ICCV
2011
IEEE
12 years 7 months ago
2011
IEEE
Recent work on unsupervised feature learning has shown that learning on polynomial expansions of input patches, such as on pair-wise products of pixel intensities, can improve the...