Trifocal Tensor and Relative Pose Estimation from 8 Lines and Known Vertical Direction
- Resource Type
- Conference
- Authors
- Guan, Banglei; Vasseur, Pascal; Demonceaux, Cedric
- Source
- 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Intelligent Robots and Systems (IROS), 2022 IEEE/RSJ International Conference on. :6001-6008 Oct, 2022
- Subject
- Bioengineering
Components, Circuits, Devices and Systems
Computing and Processing
General Topics for Engineers
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Closed-form solutions
Tensors
Pose estimation
Autonomous aerial vehicles
Autonomous automobiles
Standards
Intelligent robots
- Language
- ISSN
- 2153-0866
In this paper, we present a relative pose estimation algorithm based on lines knowing the vertical direction associated to each image. We demonstrate that a closed-form solution requiring only eight lines between three views is possible. As a linear solution, it is shown that our approach outperforms the standard trifocal estimation based on 13 triplets of lines and can be efficiently inserted into an hypothesize-and-test framework such as RANSAC. We also study our approach on different singular configurations of lines. The method is evaluated on both synthetic data and real-world sequences from KITTI and the Zürich Urban Micro Aerial Vehicle datasets. Our method is compared to 13 lines algorithm as well to points based methods such as 7-points, 5-points and 3-points.