Compression and Querying of Arbitrary Geodesic Distances

Abstract

In this paper, we propose a novel method for accelerating the computation of geodesic distances over arbitrary manifold triangulated surfaces. The method is based on a preprocessing step where we build a data structure. This allows to store arbitrary complex distance metrics. We show that, by exploiting the precomputed data, the proposed method is significantly faster than the classical Dijkstra algorithm for the com- putation of point to point distances. Moreover, as we precompute exact geodesic distances, the proposed approach can be more accurate than state-of-the-art approximations. Iciap presentation

Iciap presentation

Francesco Banterle
Francesco Banterle
Researcher

Researcher at the Visual Computing Lab

Luigi Malomo
Luigi Malomo
Researcher

Computational Fabrication

Paolo Cignoni
Paolo Cignoni
Research Director