Minimal Rolling Shutter Absolute Pose with Unknown Focal Length and Radial Distortion

Kúkelová, Zuzana; Albl, Cenek; Sugimoto, Akihiro; Schindler, Konrad; Pajdla, Tomáš

doi:10.1007/978-3-030-58558-7_41

Cited by 8 publications

(8 citation statements)

References 30 publications

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“…Then, all the camera related parameters (i.e., the rigid transformation, time offset, camera intrinsics, and RS readout time for each camera) are refined by a bundle adjustment (BA) with all the camera measurements. Kukelova et al (2020) presented the first minimal solution to absolute pose estimation of a RS camera with unknown focal length and unknown radial distortion, from seven point correspondences. With the proposed solvers they can achieve accurate solutions for camera poses, RS readout time, focal length and radial distortion.…”

Section: Camera Calibrationmentioning

confidence: 99%

Online Self-Calibration for Visual-Inertial Navigation Systems: Models, Analysis and Degeneracy

Yang¹,

Geneva²,

Zuo³

et al. 2022

Preprint

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In this paper, we study in-depth the problem of online self-calibration for robust and accurate visual-inertial state estimation. In particular, we first perform a complete observability analysis for visual-inertial navigation systems (VINS) with full calibration of sensing parameters, including IMU and camera intrinsics and IMU-camera spatial-temporal extrinsic calibration, along with readout time of rolling shutter (RS) cameras (if used). We investigate different inertial model variants containing IMU intrinsic parameters that encompass most commonly used models for low-cost inertial sensors. With these models, the state transition matrix and visual measurement Jacobians are analytically derived and the observability analysis of linearized VINS with full sensor calibration is performed. The analysis results prove that, as intuitively assumed in the literature, VINS with full sensor calibration has four unobservable directions, corresponding to the system's global yaw and translation, while all sensor calibration parameters are observable given fully-excited 6-axis motion. Moreover, we, for the first time, identify primitive degenerate motions for IMU and camera intrinsic calibration, which, when combined, may produce complex degenerate motions. This result holds true for the different inertial model variants investigated in this work and has significant impacts on practical applications of online self-calibration to many robotic platforms. Extensive Monte-Carlo simulations and real-world experiments are performed to validate both the observability analysis and identified degenerate motions, showing that online self-calibration improves system accuracy and robustness to calibration inaccuracies. We compare the proposed online self-calibration on commonly-used IMUs against the state-of-art offline calibration toolbox Kalibr, and show that the proposed system achieves better consistency and repeatability. As sensor calibration plays an important role in making real VINS work well in practice, based on our analysis and experimental evaluations, we also provide practical guidelines for how to perform online IMU-camera sensor self-calibration.

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Section: Camera Calibrationmentioning

confidence: 99%

Online Self-Calibration for Visual-Inertial Navigation Systems: Models, Analysis and Degeneracy

Yang¹,

Geneva²,

Zuo³

et al. 2022

Preprint

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“…For example, camera calibration problems, e.g. [8,9,10,11], are successfully solved by leveraging constraints of a more restrictive model. In [12], their objective is to estimate the relative motion of a vehicle from a sequence of images of a single fixed camera.…”

Section: Related Researchmentioning

confidence: 99%

HSolo: Homography from a single affine aware correspondence

Gonzales,

Monical,

Perkins

2020

Preprint

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The performance of existing robust homography estimation algorithms is highly dependent on the inlier rate of feature point correspondences. In this paper, we present a novel procedure for homography estimation that is particularly well suited for inlier-poor domains. By utilizing the scale and rotation byproducts created by affine aware feature detectors such as SIFT and SURF, we obtain an initial homography estimate from a single correspondence pair. This estimate allows us to filter the correspondences to an inlier-rich subset for use with a robust estimator. Especially at low inlier rates, our novel algorithm provides dramatic performance improvements.It's important to note that our line of research is orthogonal to these others discussed. It is quite possible to combine our outlier removal process with contemporary feature descriptors, RANSAC variants, and restricted models.

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“…This means that another radial distortion parameter can be determined when the focal length is solved. These corresponding methods are called P4Pfr solvers [18][19][20][21]. If there are five 2D-3D point correspondences, up to ten unknown parameters can be estimated.…”

Section: Introductionmentioning

confidence: 99%

“…The first category estimates the relative pose from multiple views or two cameras [6,[29][30][31][32][33][34]. The second category estimates the absolute pose from a single image [5,15,[18][19][20]35]. In this paper, we focus on the latter.…”

Section: Introductionmentioning

confidence: 99%

A New Method for Absolute Pose Estimation with Unknown Focal Length and Radial Distortion

Guo

Chen

et al. 2022

Sensors

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Estimating the absolute pose of a camera is one of the key steps for computer vision. In some cases, especially when using a wide-angle or zoom lens, the focal length and radial distortion also need to be considered. Therefore, in this paper, an efficient and robust method for a single solution is proposed to estimate the absolute pose for a camera with unknown focal length and radial distortion, using three 2D–3D point correspondences and known camera position. The problem is decomposed into two sub-problems, which makes the estimation simpler and more efficient. The first sub-problem is to estimate the focal length and radial distortion. An important geometric characteristic of radial distortion, that the orientation of the 2D image point with respect to the center of distortion (i.e., principal point in this paper) under radial distortion is unchanged, is used to solve this sub-problem. The focal length and up to four-order radial distortion can be determined with this geometric characteristic, and it can be applied to multiple distortion models. The values with no radial distortion are used as the initial values, which are close to the global optimal solutions. Then, the sub-problem can be efficiently and accurately solved with the initial values. The second sub-problem is to determine the absolute pose with geometric linear constraints. After estimating the focal length and radial distortion, the undistorted image can be obtained, and then the absolute pose can be efficiently determined from the point correspondences and known camera position using the undistorted image. Experimental results indicate this method’s accuracy and numerical stability for pose estimation with unknown focal length and radial distortion in synthetic data and real images.

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Minimal Rolling Shutter Absolute Pose with Unknown Focal Length and Radial Distortion

Cited by 8 publications

References 30 publications

Online Self-Calibration for Visual-Inertial Navigation Systems: Models, Analysis and Degeneracy

Online Self-Calibration for Visual-Inertial Navigation Systems: Models, Analysis and Degeneracy

HSolo: Homography from a single affine aware correspondence

A New Method for Absolute Pose Estimation with Unknown Focal Length and Radial Distortion

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