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

Paper i proceeding
Författare Marcus Valtonen Örnhag
Mårten Wadenbäck
Publicerad i 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
Förlag Springer
Publiceringsår 2020
Publicerad vid Institutionen för matematiska vetenskaper, Tillämpad matematik och statistik
Språk en
Länkar https://doi.org/10.1007/978-3-030-4...
Ämnesord Planar motion, Bundle adjustment, SLAM, Visual Odometry
Ämneskategorier Matematik

Sammanfattning

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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Denna text är utskriven från följande webbsida:
http://www.gu.se/forskning/publikation/?publicationId=290316
Utskriftsdatum: 2020-05-30