: Applications such as Face Recognition (FR) that deal with high-dimensional data need a mapping technique that introduces representation of low-dimensional features with enhanced ...
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
Stemming from a sound mathematical framework dating back to the beginning of the 20th century, this paper introduces a novel approach for 3D face recognition. The proposed techniqu...
The null space-based LDA takes full advantage of the null space while the other methods remove the null space. It proves to be optimal in performance. From the theoretical analysi...
Object recognition technology has matured to a point at which exciting applications are becoming possible. Indeed, industry has created a variety of computer vision products and se...