Traditional face superresolution methods treat face images as 1D vectors and apply PCA on the set of these 1D vectors to learn the face subspace. Zhang et al [7] proposed Two-dire...
This paper presents a top-down approach to 3D data analysis by fitting a Morphable Model to scans of faces. In a unified framework, the algorithm optimizes shape, texture, pose an...
In this paper, a novel personalized feature combination scheme is proposed for face verification. ANFIS (Adaptive Neuro-Fuzzy Inference System) and SVM (Support Vector Machine) ar...
In this paper, we propose a method to exploit the uniqueness in the illumination variations on the face image of a subject for face verification. Using the 3D wireframe model of a...
Most pose robust face verification algorithms, which employ 2D appearance, rely heavily on statistics gathered from offline databases containing ample facial appearance variation ...