We consider the problem of image representation and clustering. Traditionally, an n1 × n2 image is represented by a vector in the Euclidean space Rn1×n2 . Some learning algorith...
Abstract. In this paper a new method for analyzing the intrinsic dimensionality (ID) of low dimensional manifolds in high dimensional feature spaces is presented. The basic idea is...
A new method to pre-segment images by means of a hierarchical description is proposed. This description is obtained from an investigation of the deep structure of a scale space im...
Background: Accurate methods for extraction of meaningful patterns in high dimensional data have become increasingly important with the recent generation of data types containing ...
Brandon W. Higgs, Jennifer W. Weller, Jeffrey L. S...
We view the task of change detection as a problem of object recognition from learning. The object is defined in a 3D space where the time is the 3rd dimension. We propose two com...