Structure from controlled motion

TLDR

The study addresses recovering 3D structure from a single mobile camera within active vision. It proposes a revised structure‑from‑known‑motion formulation and seeks to reduce measurement‑error effects. Using this framework, the authors compute optimal camera configurations and motions, applying visual‑servoing control to robustly estimate points, lines, cylinders, spheres, etc. Real‑time experiments on points and cylinders show the active‑vision approach markedly improves estimation accuracy.

Abstract

This paper deals with the recovery of 3D information using a single mobile camera in the context of active vision. First, we propose a general revisited formulation of the structure-from-known-motion issue. Within the same formalism, we handle various kinds of 3D geometrical primitives such as points, lines, cylinders, spheres, etc. We also aim at minimizing effects of the different measurement errors which are involved in such a process. More precisely, we mathematically determine optimal camera configurations and motions which lead to a robust and accurate estimation of the 3D structure parameters. We apply the visual servoing approach to perform these camera motions using a control law in closed-loop with respect to visual data. Real-time experiments dealing with 3D structure estimation of points and cylinders are reported. They demonstrate that this active vision strategy can very significantly improve the estimation accuracy.