Accurate mirror-based camera pose estimation with explicit geometric meanings

Li, Xin; Long, Gucan; Guo, Pengyu; Liu, Jinbo; Zhang, Xiaohu; Yu, Qifeng

doi:10.1007/s11431-014-5713-z

Cited by 4 publications

(7 citation statements)

References 19 publications

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“…The mirror is uniquely determined by its unit normal vector n and the distance l with respect to fCg. 2,17 A spatial point P lies on the mirror plane if and only if it satisfies E Q -T A R G E T ; t e m p : i n t r a l i n k -; e 0 0 6 ; 6 3 ; 1 1 8 n T P ¼ l:…”

Section: Planar Mirror Reflectionmentioning

confidence: 99%

“…Then, the pose of the mirror can be calculated by Li's method. 17 For each method, 10 images are captured to estimate the mirror pose. The reflective error Es is used to evaluate the accuracy.…”

Section: Comparisonsmentioning

confidence: 99%

“…This paper is also inspired by Shah 18 and Li et al 17 Shah found the best rotation matrix with determinant 1. In contrast, we seek the best orthogonal matrix with determinant −1, and the best reflection matrix can be constructed by a matrix with determinant −1.…”

Section: Introductionmentioning

confidence: 97%

“…In Ref. 17, an accurate closed-form solution with explicit geometric meanings is proposed. It minimizes an error metric based on all reflections of rotation, and then derives the optimal solution that gives the real camera rotation directly by SVD of the sum of mirrored camera rotations.…”

Section: Introductionmentioning

confidence: 99%

“…In contrast, we seek the best orthogonal matrix with determinant −1, and the best reflection matrix can be constructed by a matrix with determinant −1. Li et al 17 calculated the camera rotation by minimizing the error of all rotation reflections. In this paper, we initialize the normal vector by minimizing the error of reflections of the unit direction vectors.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Pose estimation method for planar mirror based on one-dimensional target

Liu

2018

Opt. Eng.

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This paper presents a pose estimation method for planar mirror based on a one-dimensional (1-D) target. First, a 1-D target is maneuvered in front of a camera so as to allow the camera to capture several images of both the original and virtual feature points on the target. Next, the normal vector of the mirror and the distance between the mirror and the camera are calculated by a closed-form method. Last, a nonlinear optimization is used to refine the closed-form solution by minimizing the reprojection error of reflection projection. Synthetic data and real experiments show that the proposed method is accurate and reliable. The proposed method is simple and flexible. No prior information about the target motion and camera pose is assumed. A minimum of two nonparallel target positions are required. It is suitable for the pose estimation of planar mirrors, especially when they are in fixed positions. We can find the posture of the fixed camera according to the normal vector of the plane mirror.

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Section: Planar Mirror Reflectionmentioning

confidence: 99%

Section: Comparisonsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Pose estimation method for planar mirror based on one-dimensional target

Liu

2018

Opt. Eng.

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Pose optimization based on integral of the distance between line segments

Zhang

Liu

et al. 2015

Sci. China Technol. Sci.

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Accurate Calibration of a Large Field of View Camera with Coplanar Constraint for Large-Scale Specular Three-Dimensional Profile Measurement

Wang

Zou

2023

Sensors

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In the vision-based inspection of specular or shiny surfaces, we often compute the camera pose with respect to a reference plane by analyzing images of calibration grids, reflected in such a surface. To obtain high precision in camera calibration, the calibration target should be large enough to cover the whole field of view (FOV). For a camera with a large FOV, using a small target can only obtain a locally optimal solution. However, using a large target causes many difficulties in making, carrying, and employing the large target. To solve this problem, an improved calibration method based on coplanar constraint is proposed for a camera with a large FOV. Firstly, with an auxiliary plane mirror provided, the positions of the calibration grid and the tilt angles of the plane mirror are changed several times to capture several mirrored calibration images. Secondly, the initial parameters of the camera are calculated based on each group of mirrored calibration images. Finally, adding with the coplanar constraint between each group of calibration grid, the external parameters between the camera and the reference plane are optimized via the Levenberg-Marquardt algorithm (LM). The experimental results show that the proposed camera calibration method has good robustness and accuracy.

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Accurate mirror-based camera pose estimation with explicit geometric meanings

Cited by 4 publications

References 19 publications

Pose estimation method for planar mirror based on one-dimensional target

Pose estimation method for planar mirror based on one-dimensional target

Pose optimization based on integral of the distance between line segments

Accurate Calibration of a Large Field of View Camera with Coplanar Constraint for Large-Scale Specular Three-Dimensional Profile Measurement

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