Vector extensions for general purpose processors are an efficient feature to address the growing performance demand of multimedia and computer vision applications. Embedded proces...
Tarik Saidani, Joel Falcou, Lionel Lacassagne, Sam...
Recently, it was proven empirically that facial expressions can be modelled as isometries, that is, geodesic distances on the facial surface were shown to be significantly less se...
Alexander M. Bronstein, Michael M. Bronstein, Ron ...
This paper considers a recently proposed method for unsupervised learning and dimensionality reduction, locally linear embedding (LLE). LLE computes a compact representation of hi...
This paper introduces a new representation for planar curves. From the well-known Dirichlet problem for a disk, the harmonic function embedded in a circular disk is solely depende...
Sang-Mook Lee, A. Lynn Abbott, Neil A. Clark, Phil...
Manifold learning can discover the structure of high dimensional data and provides understanding of multidimensional patterns by preserving the local geometric characteristics. Ho...