31 search results - page 2 / 7 » Principal Manifolds and Bayesian Subspaces for Visual Recogn... |
ECCV
2000
Springer
14 years 9 months ago
2000
Springer
In recent years several techniques have been proposed for modelling the low-dimensional manifolds, or `subspaces', of natural images. Examples include principal component anal...
ACCV
2010
Springer
13 years 2 months ago
2010
Springer
Abstract. In set-based face recognition, each set of face images is often represented as a linear/nonlinear manifold and the Principal Angles (PA) or Kernel PAs are exploited to me...
ICPR
2004
IEEE
14 years 8 months ago
2004
IEEE
Bayesian analysis is a popular subspace based face recognition method. It casts the face recognition task into a binary classification problem with each of the two classes, intrap...
ICPR
2002
IEEE
14 years 8 months ago
2002
IEEE
Manifold Pursuit (MP) extends Principal Component Analysis to be invariant to a desired group of image-plane transformations of an ensemble of un-aligned images. We derive a simpl...
MM
2006
ACM
14 years 1 months ago
2006
ACM
In many image retrieval applications, the mapping between highlevel semantic concept and low-level features is obtained through a learning process. Traditional approaches often as...