224 search results - page 4 / 45 » Feature Space Hausdorff Distance for Face Recognition |
AUSAI
2005
Springer
15 years 3 months ago
2005
Springer
All the traditional PCA-based and LDA-based methods are based on the analysis of vectors. So, it is difficult to evaluate the covariance matrices in such a high-dimensional vector ...
PAMI
2008
14 years 9 months ago
2008
Face recognition algorithms perform very unreliably when the pose of the probe face is different from the gallery face: typical feature vectors vary more with pose than with identi...
ECCV
2008
Springer
15 years 11 months ago
2008
Springer
Abstract. Motivated by image perturbation and the geometry of manifolds, we present a novel method combining these two elements. First, we form a tangent space from a set of pertur...
WACV
2008
IEEE
15 years 4 months ago
2008
IEEE
Most face recognition algorithms use a “distancebased” approach: gallery and probe images are projected into a low dimensional feature space and decisions about matching are b...
CVPR
2010
IEEE
15 years 3 months ago
2010
IEEE
We introduce a novel method for face recognition from image sets. In our setting each test and training example is a set of images of an individual’s face, not just a single ima...