Generalized principal component analysis (GPCA) - introVidal, RenéMa, YiSastry, Shankar
We propose an algebraic geometric approach to the problem of estimating a mixture of linear subspaces from sample data points, the so-called generalized principal component analysis (GPCA) problem. In the absence of noise, we show that GPCA is equivalent to factoring a homogeneous polynomial whose...
A novel image compression algorithm based on generalized principal component analysis (GPCA) is proposed in this work. Each image block is first classified into a subspace and is represented with a linear combination of the basis vectors for the subspace. Therefore, the encoded information consists ...
Abstract Recently, principal component analysis (PCA) has made remarkable progress in some research areas including computer vision and pattern recognition. The objects handled by PCA have been extended from vectors to higher-order tensors, also known as multidimensional orN-way arrays including vectors...
Generalized principal component analysis (gpca). In Proceedings of the 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, volume 1, pages 621-628, Madison, Wisconsin, USA, June 2003.R. Vidal, Y. Ma, and S. Sastry. Generalized principal component analysis (GPCA)....
VIDAL RE.Generalized Principal Component Analysis(GPCA):an Algebraic Geometric Approach to Subspace Clustering and Motion Segmentation[D].PhD thesis,University of California at Berkeley,2003.R. Vidal, "Generalized principal component analysis (gpca): an algebraic geometric approach to subspace...
A generalization of principal component analysis to K sets of variables The aim of this paper is to introduce a new method, generalized principal component analysis (GPCA), which is a generalization of principal component analy... P Casin - 《Computational Statistics & Data Analysis》 被引量: ...
We also present applications of GPCA to computer vision problems such as face clustering, temporal video segmentation, and 3D motion segmentation from point correspondences in multiple affine views. 展开 关键词: dynamic scenes and motion segmentation Index Terms- Principal component analysis (PCA ...
Generalized principal component analysis (GPCA) has been an active area of research in statistical signal processing for decades. It is used, e.g., for denoising in subspace tracking as the noise of different nature is incorporated into the procedure of maximizing signal-noise ratio (SNR). This...
Generalized Principal Component Analysis ( GPCA ) ∗ 2 Problem formulation and analysisSastry, Shankar