Embedding images into a low dimensional space has a wide range of applications: visualization, clustering, and pre-processing for supervised learning. Traditional dimension reduct...
In this paper novel theory to automate shape modelling is described. The main idea is to develop a theory that is intrinsically defined for curves, as opposed to a finite sample o...
We present a novel dynamic programming framework that allows one to compute tight upper bounds for the p-values of gapped local alignments in pseudo–polynomial time. Our algorith...
— In many computer vision related applications it is necessary to distinguish between the background of an image and the objects that are contained in it. This is a difficult pr...
Thiago C. Bellardi, Dizan Vasquez, Christian Laugi...
Abstract. In this work, we present two active shape models for the segmentation of tubular objects. The first model is built using cylindrical parameterization and minimum descrip...