We introduce Localized Components Analysis (LoCA) for describing surface shape variation in an ensemble of biomedical objects using a linear subspace of spatially localized shape c...
Dan A. Alcantara, Owen T. Carmichael, Eric Delson,...
Appearance Models (AM) are commonly used to model appearance and shape variation of objects in images. In particular, they have proven useful to detection, tracking, and synthesis...
Fernando De la Torre, Alvaro Collet, Manuel Quero,...
We consider feature extraction (dimensionality reduction) for compositional data, where the data vectors are constrained to be positive and constant-sum. In real-world problems, t...
Majority of practical multivariate statistical analyses and optimizations model interdependence among random variables in terms of the linear correlation among them. Though linear...
Parameterized Appearance Models (PAMs) (e.g. eigentracking, active appearance models, morphable models) use Principal Component Analysis (PCA) to model the shape and appearance of...