Direct Pose Estimation with a Monocular Camera

TL;DR

This paper introduces a direct monocular camera pose estimation method that calculates 6DoF motion without prior scene knowledge, providing real-time metric position and rotation with a quality measure for improved navigation.

Contribution

It presents a novel direct approach for monocular pose estimation that does not require prior scene information and includes a quality measure for the estimated motion.

Findings

Accurate 6DoF pose estimation from two images without scene knowledge

Provides a quality measure for motion parameters

Validated on real scene images

Abstract

We present a direct method to calculate a 6DoF pose change of a monocular camera for mobile navigation. The calculated pose is estimated up to a constant unknown scale parameter that is kept constant over the entire reconstruction process. This method allows a direct cal- culation of the metric position and rotation without any necessity to fuse the information in a probabilistic approach over longer frame sequence as it is the case in most currently used VSLAM approaches. The algorithm provides two novel aspects to the field of monocular navigation. It allows a direct pose estimation without any a-priori knowledge about the world directly from any two images and it provides a quality measure for the estimated motion parameters that allows to fuse the resulting information in Kalman Filters. We present the mathematical formulation of the approach together with experimental validation on real scene images.