Topological And Geometrical Reasoning In 3D Grouping for Reconstructing Polyhedral Surfaces

Abstract

We are developing a system for reconstructing polyhedral surfaces from multiple images. This process can take advantage of the topological relations of the observed image features triggering and therefore speeding up the grouping of features to polyhedral surfaces. Exploiting the statistical properties of features when grouping them leads to consistent decisions being invariant to numbering and choice of coordinate system and allows statistical testing. This simplifies the choice of thresholds to the definition of a scene independent significance level. We decribe the topological and statistical models used within our system. Experiments with synthetic and real data prove the feasibility of the approach. y 1 INTRODUCTION Reconstructing polyhedral surfaces from multiple images is a classical task in Computer Vision. In case of controlled environment solutions are quite far advanced. However, in outdoor environments, e. g. when tracking vehicles or when reconstructing buildings, system..