This paper examines the the effectiveness of feature modelling to conduct 2D and 3D face recognition. In particular, PCA difference vectors are modelled using Gaussian Mixture Mod...
Chris McCool, Jamie Cook, Vinod Chandran, Sridha S...
In this paper two methods for human face recognition and the influence of location mistakes are shown. First one, Principal Components Analysis (PCA), has been one of the most appl...
2D intensity images and 3D shape models are both useful for face recognition, but in different ways. While algorithms have long been developed using 2D or 3D data, recently has see...
In this paper, we propose an original framework for representing 2D and 3D face information using geodesic distances. This aims to define a representation enabling the direct com...
Stefano Berretti, Alberto Del Bimbo, Pietro Pala, ...
We present an automatic disparity-based approach for 3D face modeling, from two frontal and one profile view stereo images, for 3D face recognition applications. Once the images a...
A-Nasser Ansari, Mohamed Abdel-Mottaleb, Mohammad ...