基于旋转搜索的相机位姿估计和对应点匹配

doi:10.7527/S1000-6893.2022.26695

Abstract

Abstract:

The traditional Simultaneous Pose and Correspondence Determination （SPCD） algorithm uses a two-stage alternate iteration strategy to calculate the camera pose， which leads to poor accuracy. Besides， the traditional SPCD algorithm relies on local search strategies， and have no guarantee of finding the globally optimal solution. To improve the accuracy and the ability of global convergence of solving the SPCD problem， a new solving model based on point-to-point constraints is derived for the SPCD problem in this paper. Based on this new model， an optimal objective function is constructed by using the angle distance， and the branch-and-bound method is used to search the optimal camera pose and the 3D/2D correspondences. Experiments show that the proposed method has higher accuracy and convergence rate compared to the traditional SoftPOSIT algorithm， and would have wide applications.

Key words: computer vision, vision-based navigation, vision measurement, pose estimation, PnP problem, Simultaneous Pose and Correspondence Determination (SPCD) problem

CLC Number:

V448

Ping WANG, Hui FU, Guili XU. Camera pose estimation and corresponding points matching based on rotation search[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2023, 44(2): 326695-326695.

Figures/Tables 13

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Fig. 8

Fig. 9

Fig. 10

Table 1

Camera calibration result

参数

结果

焦距

f x =

2 223.918 50，

f y =

2 223.583 81

主点

（C_x， C_y ）=（660.599 81， 504.946 03）

畸变系数

$k 1 =$ -0.118 97， $k 2 =$ 0.289 95，

$p 1 =$ -0.000 44， $p 2 =$ 0.002 79

Table 1

Fig. 11

Fig. 12

References 28

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Camera pose estimation and corresponding points matching based on rotation search

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