We investigate reducing the dimensionality of image sets by using principal component analysis on wavelet coefficients to maximize edge energy in the reduced dimension images. Lar...
This paper introduces a multilinear principal component analysis (MPCA) framework for tensor object feature extraction. Objects of interest in many computer vision and pattern rec...
Haiping Lu, Konstantinos N. Plataniotis, Anastasio...
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...
Skew detection via principal components is proposed as an e ective methodforimageswhich contain other parts than text. It is shown that the negative of the image leads to much mor...
In this paper, we propose an unsupervised approach for identifying bipolar person names in a set of topic documents. We employ principal component analysis (PCA) to discover bipol...