Relative Pose Estimation for Stereo Rolling Shutter Cameras

TL;DR

This paper introduces a linear algorithm for estimating the 6 DoF relative pose of stereo rolling shutter cameras using consecutive frames, enabling image correction without scene assumptions.

Contribution

A novel linear method for relative pose estimation of stereo RS cameras that leverages depth maps and constant velocity motion assumptions.

Findings

Effective in simulated point experiments

Accurate in synthetic RS image tests

Enables RS image undistortion without scene assumptions

Abstract

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.