In this paper, we present a novel linear algorithm to estimate the 6 DoF relative pose from consecutive frames of stereo rolling shutter (RS) cameras. Our method is derived based on the assumption that stereo cameras undergo motion with constant velocity around the center of the baseline, which needs 9 pairs of correspondences on both left and right consecutive frames. The stereo RS images enable the recovery of depth maps from the semi-global matching (SGM) algorithm. With the estimated camera motion and depth map, we can correct the RS images to get the undistorted images without any scene structure assumption. Experiments on both simulated points and synthetic RS images demonstrate the effectiveness of our algorithm in relative pose estimation.
@article{arxiv.2006.07807,
title = {Relative Pose Estimation for Stereo Rolling Shutter Cameras},
author = {Ke Wang and Bin Fan and Yuchao Dai},
journal= {arXiv preprint arXiv:2006.07807},
year = {2020}
}
Comments
Accepted by International Conference on Image Processing (ICIP 2020)