TY - GEN
T1 - Efficient Bundle Adjustment for Coplanar Points and Lines
AU - Zhou, Lipu
AU - Liu, Jiacheng
AU - Zhai, Fengguang
AU - Ai, Pan
AU - Ren, Kefei
AU - Mao, Yinian
AU - Huang, Guoquan
AU - Meng, Ziyang
AU - Kaess, Michael
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Bundle adjustment (BA) is a well-studied fundamental problem in the robotics and vision community. In man-made environments, coplanar points and lines are ubiquitous. However, the number of works on bundle adjustment with coplanar points and lines is relatively small. This paper focuses on this special BA problem, referred to as πBA. For a point or a line on a plane, we derive a new constraint to describe the relationship among two poses and the plane, called π-constraint. We distribute π-constraints into different groups. Each group is called a π-factor. We prove that, with some simple preprocessing, the computational complexity associated with a π-factor in the Levenberg-Marquardt (LM) algorithm is O(1), independent of the number of π-constraints packed into the π-factor. In π-BA, π-factors replace original reprojection errors. One problem is how to divide π-constraints into π-factors. Different strategies may result in different numbers of π-factors, which in turn affects the efficiency. It is difficult to get the optimal division. We present a greedy algorithm to overcome this problem. Experimental results verify that our algorithm can significantly accelerate the computation.
AB - Bundle adjustment (BA) is a well-studied fundamental problem in the robotics and vision community. In man-made environments, coplanar points and lines are ubiquitous. However, the number of works on bundle adjustment with coplanar points and lines is relatively small. This paper focuses on this special BA problem, referred to as πBA. For a point or a line on a plane, we derive a new constraint to describe the relationship among two poses and the plane, called π-constraint. We distribute π-constraints into different groups. Each group is called a π-factor. We prove that, with some simple preprocessing, the computational complexity associated with a π-factor in the Levenberg-Marquardt (LM) algorithm is O(1), independent of the number of π-constraints packed into the π-factor. In π-BA, π-factors replace original reprojection errors. One problem is how to divide π-constraints into π-factors. Different strategies may result in different numbers of π-factors, which in turn affects the efficiency. It is difficult to get the optimal division. We present a greedy algorithm to overcome this problem. Experimental results verify that our algorithm can significantly accelerate the computation.
UR - https://www.scopus.com/pages/publications/85168705186
U2 - 10.1109/ICRA48891.2023.10160834
DO - 10.1109/ICRA48891.2023.10160834
M3 - 会议稿件
AN - SCOPUS:85168705186
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 8356
EP - 8363
BT - Proceedings - ICRA 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE International Conference on Robotics and Automation, ICRA 2023
Y2 - 29 May 2023 through 2 June 2023
ER -