In the past few years, some nonlinear dimensionality reduction (NLDR) or nonlinear manifold learning methods have aroused a great deal of interest in the machine learning communit...
Algorithms for nonlinear dimensionality reduction (NLDR) find meaningful hidden low-dimensional structures in a high-dimensional space. Current algorithms for NLDR are Isomaps, Loc...
Location information is very useful in the design of sensor network infrastructures. In this paper, we study the anchor-free 2D localization problem by using local angle measureme...
Abstract. In this paper we present a novel tool for body-part segmentation and tracking in the context of multiple camera systems. Our goal is to produce robust motion cues over ti...
Fabio Cuzzolin, Diana Mateus, Edmond Boyer, Radu H...
In recent work, several supervised spectral embedding procedures have been proposed. Although experimentally validated, the construction of these algorithms was rather ad hoc. Thi...