Volume XLII-1/W1
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1/W1, 41-46, 2017
https://doi.org/10.5194/isprs-archives-XLII-1-W1-41-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1/W1, 41-46, 2017
https://doi.org/10.5194/isprs-archives-XLII-1-W1-41-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

  30 May 2017

30 May 2017

RELATIVE CAMERA POSE ESTIMATION METHOD USING OPTIMIZATION ON THE MANIFOLD

C. Cheng1, X. Hao1, and J. Li1,2 C. Cheng et al.
  • 1School of Navigation and Aerospace Engineering, Information Engineering University, Zhengzhou 450001, China
  • 2Institute of Photogrammetry and GeoInformation, Leibniz Universität Hannover, Germany

Keywords: Pose Estimation, Optimization, Manifold, Lie Group/Algebra, Levenberg-Marquardt

Abstract. To solve the problem of relative camera pose estimation, a method using optimization with respect to the manifold is proposed. Firstly from maximum-a-posteriori (MAP) model to nonlinear least squares (NLS) model, the general state estimation model using optimization is derived. Then the camera pose estimation model is applied to the general state estimation model, while the parameterization of rigid body transformation is represented by Lie group/algebra. The jacobian of point-pose model with respect to Lie group/algebra is derived in detail and thus the optimization model of rigid body transformation is established. Experimental results show that compared with the original algorithms, the approaches with optimization can obtain higher accuracy both in rotation and translation, while avoiding the singularity of Euler angle parameterization of rotation. Thus the proposed method can estimate relative camera pose with high accuracy and robustness.