Two-dimensional principal component analysis (2DPCA) is based on the 2D images rather than 1D vectorized images like PCA, which is a classical feature extraction technique in face...
In this paper, we propose a novel learned visual codebook (LVC) for 3D face recognition. In our method, we first extract intrinsic discriminative information embedded in 3D faces...
A fully automatic 3D face recognition algorithm is presented. Several novelties are introduced to make the recognition robust to facial expressions and efficient. These novelties...
A novel algorithm for 3D face recognition based point cloud rotations, multiple projections, and voted keypoint matching is proposed and evaluated. The basic idea is to rotate eac...
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 ...