Direct Pose Estimation with a Monocular Camera
Darius Burschka, Elmar Mair

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…
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Taxonomy
TopicsRobotics and Sensor-Based Localization · Advanced Vision and Imaging · Advanced Image and Video Retrieval Techniques
