We consider a setting for discriminative semisupervised learning where unlabeled data are used with a generative model to learn effective feature representations for discriminativ...
Active shape model (ASM) statistically represents a shape by a set of well-defined landmark points and models object variations using principal component analysis (PCA). However, ...
The length of the room impulse response characterizing the acoustic path between speaker and microphone is significantly larger than the length of the analysis window used for fea...
Efficient and accurate fitting of Active Appearance
Models (AAM) is a key requirement for many applications.
The most efficient fitting algorithm today is Inverse Compositional
...
Brian Amberg (University of Basel), Andrew Blake (...
Parametric models of shape and texture such as Active Appearance Models (AAMs) are diverse tools for deformable object appearance modeling and have found important applications in...