1088 search results - page 7 / 218 » Robust Principal Component Analysis for Computer Vision |
JACM
2011
12 years 10 months ago
2011
This paper is about a curious phenomenon. Suppose we have a data matrix, which is the superposition of a low-rank component and a sparse component. Can we recover each component i...
NIPS
2008
13 years 9 months ago
2008
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...
CVPR
2003
IEEE
14 years 9 months ago
2003
IEEE
When performing subspace modelling of data using Principal Component Analysis (PCA) it may be desirable to constrain certain directions to be more meaningful in the context of the...
ICASSP
2011
IEEE
12 years 11 months ago
2011
IEEE
Face verification systems reach good performance on ideal environmental conditions. Conversely, they are very sensitive to non-controlled environments. This work proposes the cla...
ICC
2008
IEEE
14 years 1 months ago
2008
IEEE
—One of the major threats to cyber security is the Distributed Denial-of-Service (DDoS) attack. In our previous projects, PacketScore, ALPi, and other statistical filtering-based...