Dimensionality reduction is a statistical tool commonly used to map high-dimensional data into lower a dimensionality. The transformed data is typically more suitable for regressi...
Bill Kapralos, Nathan Mekuz, Agnieszka Kopinska, S...
In this work we present an efficient coding scheme suitable for lossy image compression using a lattice vector quantizer (LVQ) based on statistically independent data projections...
Leonardo H. Fonteles, Marc Antonini, Ronald Phlypo
In many cases, normal uses of a system form patterns that will repeat. The most common patterns can be collected into a prediction model which will essentially predict that usage p...
Many of the computer vision algorithms have been posed in various forms of differential equations, derived from minimization of specific energy functionals, and the finite eleme...
In this paper we introduce a new surface representation, the displaced subdivision surface. It represents a detailed surface model as a scalar-valued displacement over a smooth do...