A general solution to the P4P problem for camera with unknown focal length

Bujnak, Martin; Kúkelová, Zuzana; Pajdla, Tomáš

doi:10.1109/cvpr.2008.4587793

Cited by 153 publications

(142 citation statements)

References 23 publications

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“…For the minimal pose solver, we use the 3-point algorithm if the focal length is approximately known, e.g., from EXIF data, or the 4-point algorithm [30] if the focal length is unknown and needs to be estimated along with the extrinsics. Finally a local bundle adjustment is used to refine the pose.…”

Section: Experiments and Resultsmentioning

confidence: 99%

Worldwide Pose Estimation Using 3D Point Clouds

Liu

Snavely

Huttenlocher

et al. 2016

Large-Scale Visual Geo-Localization

131

268

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Abstract. We address the problem of determining where a photo was taken by estimating a full 6-DOF-plus-intrincs camera pose with respect to a large geo-registered 3D point cloud, bringing together research on image localization, landmark recognition, and 3D pose estimation. Our method scales to datasets with hundreds of thousands of images and tens of millions of 3D points through the use of two new techniques: a co-occurrence prior for RANSAC and bidirectional matching of image features with 3D points. We evaluate our method on several large data sets, and show state-of-the-art results on landmark recognition as well as the ability to locate cameras to within meters, requiring only seconds per query.

show abstract

Section: Experiments and Resultsmentioning

confidence: 99%

Worldwide Pose Estimation Using 3D Point Clouds

Liu

Snavely

Huttenlocher

et al. 2016

Large-Scale Visual Geo-Localization

131

268

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show abstract

“…Such systematic generation of polynomials q i results in many unnecessary polynomials, many of which can be eliminated afterwards in a simple and intuitive way [5]. The method starts with the matrix M, which has the property that after its G-J elimination all polynomials q i necessary for constructing the action matrix are obtained.…”

Section: Gröbner Basis Solvermentioning

confidence: 99%

“…The action matrix will than contain coefficients from these rows which correspond to the monomials from the basis B and will have the form (5).…”

Section: Construction the Action Matrixmentioning

confidence: 99%

“…The solver typically consists of hand made elimination templates [18,19,9,11] (or one template [2][3][4][5]) that determine which polynomials from the ideal I should be added to the initial equations to obtain the Gröbner basis G or at least all polynomials needed for constructing the action matrix M f . These elimination templates are the crucial part of the solver.…”

Section: Gröbner Basis Solvermentioning

confidence: 99%

See 1 more Smart Citation

Automatic Generator of Minimal Problem Solvers

Kúkelová

Bujnak

Pajdla

2008

Lecture Notes in Computer Science

Self Cite

187

280

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Abstract. Finding solutions to minimal problems for estimating epipolar geometry and camera motion leads to solving systems of algebraic equations. Often, these systems are not trivial and therefore special algorithms have to be designed to achieve numerical robustness and computational efficiency. The state of the art approach for constructing such algorithms is the Gröbner basis method for solving systems of polynomial equations. Previously, the Gröbner basis solvers were designed ad hoc for concrete problems and they could not be easily applied to new problems. In this paper we propose an automatic procedure for generating Gröbner basis solvers which could be used even by non-experts to solve technical problems. The input to our solver generator is a system of polynomial equations with a finite number of solutions. The output of our solver generator is the Matlab or C code which computes solutions to this system for concrete coefficients. Generating solvers automatically opens possibilities to solve more complicated problems which could not be handled manually or solving existing problems in a better and more efficient way. We demonstrate that our automatic generator constructs efficient and numerically stable solvers which are comparable or outperform known manually constructed solvers. The automatic generator is available at http://cmp.felk.cvut.cz/minimal 3 .

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“…When a monocular vision system and a known object are used, the problem is well known as PnP (Perspective-nPoints) [4][5][6][7]. In this case, the matching between known 3D points and their projection in the image allows to deduce the pose.…”

Section: Introductionmentioning

confidence: 99%

Circular Laser/Camera-Based Attitude and Altitude Estimation: Minimal and Robust Solutions

et al. 2017

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This paper proposes a basic structured light system for pose estimation. It consists of a circular laser pattern and a camera rigidly attached to the laser source. We develop a geometric modeling that allows to efficiently estimate the pose at scale of the system, relative to a reference plane onto which the pattern is projected. Three different robust estimation strategies, including two minimal solutions, are also presented with this geometric formulation. Synthetic and real experiments are performed for a complete evaluation, both quantitatively and qualitatively, according to different scenarios and environments. We also show that the system can be embedded for UAV experiments.

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A general solution to the P4P problem for camera with unknown focal length

Abstract: Abstract

Cited by 153 publications

References 23 publications

Worldwide Pose Estimation Using 3D Point Clouds

Worldwide Pose Estimation Using 3D Point Clouds

Automatic Generator of Minimal Problem Solvers

Circular Laser/Camera-Based Attitude and Altitude Estimation: Minimal and Robust Solutions

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