Pose Estimation of Free-Form Objects

Abstract

In this contribution we present an approach for 2D-3D pose estimation of 3D free-form surface models. In our scenario we observe a free-form object in an image of a calibrated camera. Pose estimation means to estimate the relative position and orientation of the 3D object to the reference camera system. The object itself is modeled as a two-parametric 3D surface and extended by one-parametric contour parts of the object. A twist representation, which is equivalent to a Fourier representation allows for a low-pass approximation of the object model, which is advantageously applied to regularize the pose problem. The experiments show, that our developed algorithms are fast (200ms/frame) and accurate (1^ o rotational error/frame).