To reconstruct the shape of objects from incomplete point sets or noisy images, robust and accurate reconstruction methods are required. This paper presents a physics-based approa...
In this paper we propose an inexact spectral matching algorithm that embeds large graphs on a low-dimensional isometric space spanned by a set of eigenvectors of the graph Laplacia...
David Knossow, Avinash Sharma, Diana Mateus, Radu ...
In arbitrary dimension, we consider the semi-discrete elliptic operator -2 t + AM , where AM is a finite difference approximation of the operator - x((x) x). For this operator we d...
We propose a novel stochastic graph matching algorithm based on data-driven Markov Chain Monte Carlo (DDMCMC) sampling technique. The algorithm explores the solution space efficien...
This paper investigates compression of 3D objects in computer graphics using manifold learning. Spectral compression uses the eigenvectors of the graph Laplacian of an object'...