Enforcing the General Planar Motion Model: Bundle Adjustment for Planar Scenes
Paper i proceeding, 2020

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.

bundle adjustment

planar motion

visual odometry

slam

Författare

Marcus Valtonen Örnhag

Lunds tekniska högskola

Mårten Wadenbäck

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

03029743 (ISSN) 16113349 (eISSN)

Vol. 11996 119-135

The International Conference on Pattern Recognition Applications and Methods (ICPRAM 2019)
Prague, Czech Republic,

Styrkeområden

Informations- och kommunikationsteknik

Ämneskategorier

Systemvetenskap

Datavetenskap (datalogi)

Datorsystem

DOI

10.1007/978-3-030-40014-9_6

Mer information

Skapat

2020-02-17