Abstract--High-dimensional data are common in many domains, and dimensionality reduction is the key to cope with the curse-of-dimensionality. Linear discriminant analysis (LDA) is ...
Facial expression recognition is a topic of interest both in industry and academia. Recent approaches to facial expression recognition are based on mapping expressions to low dime...
We develop a supervised dimensionality reduction method, called Lorentzian Discriminant Projection (LDP), for feature extraction and classification. Our method represents the str...
A new method for classification is proposed. This is based on kernel orthonormalized partial least squares (PLS) dimensionality reduction of the original data space followed by a ...
This paper introduces a framework that employs the Fisher linear discriminant model (FLDM) and classifier (FLDC) on integrated facial appearance and facial expression features. T...
Pohsiang Tsai, Tich Phuoc Tran, Tom Hintz, Tony Ja...