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Enforcing the General Planar Motion Model: Bundle Adjustment for Planar Scenes

Conference paper
Authors Marcus Valtonen Örnhag
Mårten Wadenbäck
Published in International Conference on Pattern Recognition Applications and Methods, ICPRAM 2019. Pattern Recognition Applications and Methods, Lecture Notes in Computer Science, vol 11996
ISBN 978-3-030-40013-2
Publisher Springer
Publication year 2020
Published at Department of Mathematical Sciences, Applied Mathematics and Statistics
Language en
Keywords Planar motion, Bundle adjustment, SLAM, Visual Odometry
Subject categories Mathematics


In this paper we consider the case of planar motion, where a mobile platform equipped with two cameras moves freely on a planar surface. The cameras are assumed to be directed towards the floor, as well as being connected by a rigid body motion, which constrains the relative motion of the cameras and introduces new geometric constraints. In the existing literature, there are several algorithms available to obtain planar motion compatible homographies. These methods, however, do not minimise a physically meaningful quantity, which may lead to issues when tracking the mobile platform globally. As a remedy, we propose a bundle adjustment algorithm tailored for the specific problem geometry. Due to the new constrained model, general bundle adjustment frameworks, compatible with the standard six degree of freedom model, are not directly applicable, and we propose an efficient method to reduce the computational complexity, by utilising the sparse structure of the problem. We explore the impact of different polynomial solvers on synthetic data, and highlight various trade-offs between speed and accuracy. Furthermore, on real data, the proposed method shows an improvement compared to generic methods not enforcing the general planar motion model.

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