The FERET evaluation compared recognition rates for different semi-automated and automated face recognition algorithms. We extend FERET by considering when differences in recognit...
J. Ross Beveridge, Kai She, Bruce A. Draper, Geof ...
: 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 ...
In 3D face recognition systems, 3D facial shape information plays an important role. 3D face recognizers usually depend on point cloud representation of faces where faces are repre...
Dimensionality reduction is an important issue when facing high-dimensional data. For supervised dimensionality reduction, Linear Discriminant Analysis (LDA) is one of the most po...
Feiping Nie, Shiming Xiang, Yangqiu Song, Changshu...
Recognising face with large pose variation is more challenging than that in a fixed view, e.g. frontal-view, due to the severe non-linearity caused by rotation in depth, selfshadi...