This paper develops a classification algorithm in the framework of spectral graph theory where the underlying manifold of a high dimensional data set is described by a graph. The...
Existing work for query processing over graph data models often relies on pre-computing the transitive closure or path indexes. In this paper, we propose a family of stack-based a...
In this work we address the general bin-picking problem where 3D data is available. We apply Harmonic Shape Contexts (HSC) features since these are invariant to translation, scale...
Abstract. This paper presents an approach based on graph cuts initially used for motion segmentation that is being applied to the nonrigid registration problem. The main contributi...
We argue that a comprehensive model of graph comprehension must include spatial cognition. We propose that current models of graph comprehension have not needed to incorporate spat...