Learning models for detecting and classifying object categories is a challenging problem in machine vision. While discriminative approaches to learning and classification have, in...
—In this paper, we present a novel image classification system that is built around a core of trainable filter ensembles that we call Volterra kernel classifiers. Our system trea...
Ritwik Kumar, Arunava Banerjee, Baba C. Vemuri, Ha...
This paper describes a novel Gabor Feature Class$er (GFC)method forface recognition. The GFC method employs an enhanced Fisher discrimination model on an augmented Gabor feature v...
Abstract. In set-based face recognition, each set of face images is often represented as a linear/nonlinear manifold and the Principal Angles (PA) or Kernel PAs are exploited to me...
In this paper we present a novel face classification system
where we represent face images as a spatial arrangement
of image patches, and seek a smooth non-linear functional
map...