Image auto-annotation is a challenging task in computer vision. The goal of this task is to predict multiple words for generic images automatically. Recent state-of-theart methods...
This paper proposes a general method for improving image descriptors using discriminant projections. Two methods based on Linear Discriminant Analysis have been recently introduce...
In this paper we present the results of a comparative study of linear and kernel-based methods for face recognition. The methods used for dimensionality reduction are Principal Co...
Himaanshu Gupta, Amit K. Agrawal, Tarun Pruthi, Ch...
We study the use of kernel subspace methods that learn low-dimensional subspace representations for classification tasks. In particular, we propose a new method called kernel weigh...
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...