IMU-aligned Camera Egomotion

Efficient Solutions for Homography-based Camera Pose Estimation with an IMU Common Direction

— In this work, we propose a novel approach to two-view minimal-case relative pose problems based on homography with a common reference direction. We explore the rank-1 constraint on the difference between the Euclidean homography matrix and the corresponding rotation, and propose an efficient two-step solution for solving both the calibrated and partially calibrated (unknown focal length) problems. We derive new 3.5-point, 3.5-point, 4-point solvers for two cameras such that the two focal lengths are unknown but equal, one of them is unknown, and both are unknown and possibly different, respectively. We present detailed analyses and comparisons with existing 6 and 7-point solvers, including results with smart phone images. Cheers!

Reference paper:

• Yaqing Ding, Jian Yang, Jean Ponce and Hui Kong, An efficient solution to the homography-based relative pose problem with a common reference direction, IEEE International Conference on Computer Vision (ICCV) 2019 (Oral presentation)

• Yaqing Ding, Jian Yang, Jean Ponce, and Hui Kong, Homography-Based Minimal-Case Relative Pose Estimation with Known Gravity Direction, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020