A robust direct linear transformation for camera pose estimation using points

被引:3
作者
Wang, Ping [1 ,2 ]
Jiao, Boqiao [1 ]
Yao, Pengpeng [3 ]
Wei, Xiaoyuan [1 ]
Zhang, Aihua [1 ]
机构
[1] Lanzhou Univ Technol, Coll Elect & Informat Engn, Lanzhou 730050, Peoples R China
[2] Key Lab Gansu Adv Control Elect & Control Engn, Lanzhou 730050, Peoples R China
[3] Zhuhai Fudan Innovat Inst, Zhuhai, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
Perspective-n-point problem (P n P); Relative position and attitude; Pose estimation; Monocular vision; Vision-based navigation; Computer vision; EFFICIENT SOLUTION; OPTIMIZATION; ALGORITHM; ACCURATE;
D O I
10.1016/j.imavis.2023.104883
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Camera pose estimation from 3D points and their 2D projections, known as the perspective-n-point (PnP) problem, is a fundamental task in computer vision. In this paper, we propose a robust direct linear transformation method for the PnP problem. The novelty lies in that a plane constraint based on the pinhole camera model is introduced, and an over-constrained linear equation system is obtained by merging the linear form of both the measured point correspondences and the plane constraint. As a result, our method successfully reduces the minimal number of point correspondences required by the linear solver to 4, and yields a unique solution for 4point, 5-point, and n-point pose estimation. Experiment results, using both synthetic and real data, show that our method is substantially faster, and offers the accuracy and precision comparable with that of state-of-the-art methods.
引用
收藏
页数:12
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