Globally Optimal Multi-Scale Monocular Hand-Eye Calibration Using Dual Quaternions

• URL: http://arxiv.org/abs/2201.04473v1
• Date: Wed, 12 Jan 2022 13:48:04 GMT
• Title: Globally Optimal Multi-Scale Monocular Hand-Eye Calibration Using Dual Quaternions
• Authors: Thomas Wodtko, Markus Horn, Michael Buchholz, Klaus Dietmayer
• Abstract summary: We present an approach for monocular hand-eye calibration from per-sensor ego-motion based on dual quaternions. Our algorithms are evaluated and compared to state-of-the-art approaches on simulated and real-world data.
• Score: 9.287964414592826
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this work, we present an approach for monocular hand-eye calibration from per-sensor ego-motion based on dual quaternions. Due to non-metrically scaled translations of monocular odometry, a scaling factor has to be estimated in addition to the rotation and translation calibration. For this, we derive a quadratically constrained quadratic program that allows a combined estimation of all extrinsic calibration parameters. Using dual quaternions leads to low run-times due to their compact representation. Our problem formulation further allows to estimate multiple scalings simultaneously for different sequences of the same sensor setup. Based on our problem formulation, we derive both, a fast local and a globally optimal solving approach. Finally, our algorithms are evaluated and compared to state-of-the-art approaches on simulated and real-world data, e.g., the EuRoC MAV dataset.

Related papers

• Superresolution in separation estimation between two dynamic incoherent sources using spatial demultiplexing [0.0]
  Recently, perfect measurement based on spatial mode demultiplexing (SPADE) in Hermite-Gauss modes allowed one to reach the quantum limit of precision for estimation of separation between two weak incoherent stationary sources. In this paper, we consider another deviation from the perfect setup by discarding the assumption about the stationarity of the sources. We formulate a measurement algorithm that allows for the reduction of one parameter for estimation in the stationary sources scenario.
  arXiv  Detail & Related papers  (2024-07-15T07:57:57Z)
• An Accurate and Real-time Relative Pose Estimation from Triple Point-line Images by Decoupling Rotation and Translation [10.05584976985694]
  3D-2D constraints provided by line features have been widely used in Visual Odometry (VO) and Structure-from-Motion (SfM) systems. We propose a novel three-view pose solver based on rotation-translation decoupled estimation.
  arXiv  Detail & Related papers  (2024-03-18T10:21:05Z)
• Q-SLAM: Quadric Representations for Monocular SLAM [85.82697759049388]
  We reimagine volumetric representations through the lens of quadrics. We use quadric assumption to rectify noisy depth estimations from RGB inputs. We introduce a novel quadric-decomposed transformer to aggregate information across quadrics.
  arXiv  Detail & Related papers  (2024-03-12T23:27:30Z)
• Joint Spatial-Temporal Calibration for Camera and Global Pose Sensor [0.4143603294943439]
  In robotics, motion capture systems have been widely used to measure the accuracy of localization algorithms. These functionalities require having accurate and reliable spatial-temporal calibration parameters between the camera and the global pose sensor. In this study, we provide two novel solutions to estimate these calibration parameters.
  arXiv  Detail & Related papers  (2024-03-01T20:56:14Z)
• Vanishing Point Estimation in Uncalibrated Images with Prior Gravity Direction [82.72686460985297]
  We tackle the problem of estimating a Manhattan frame. We derive two new 2-line solvers, one of which does not suffer from singularities affecting existing solvers. We also design a new non-minimal method, running on an arbitrary number of lines, to boost the performance in local optimization.
  arXiv  Detail & Related papers  (2023-08-21T13:03:25Z)
• A Model for Multi-View Residual Covariances based on Perspective Deformation [88.21738020902411]
  We derive a model for the covariance of the visual residuals in multi-view SfM, odometry and SLAM setups. We validate our model with synthetic and real data and integrate it into photometric and feature-based Bundle Adjustment.
  arXiv  Detail & Related papers  (2022-02-01T21:21:56Z)
• Calibrated and Partially Calibrated Semi-Generalized Homographies [65.29477277713205]
  We propose the first minimal solutions for estimating the semi-generalized homography given a perspective and a generalized camera. The proposed solvers are stable and efficient as demonstrated by a number of synthetic and real-world experiments.
  arXiv  Detail & Related papers  (2021-03-11T08:56:24Z)
• Globally Optimal Relative Pose Estimation with Gravity Prior [63.74377065002315]
  Smartphones, tablets and camera systems used, e.g., in cars and UAVs, are typically equipped with IMUs that can measure the gravity vector accurately. We propose a novel globally optimal solver, minimizing the algebraic error in the least-squares sense, to estimate the relative pose in the over-determined pose. The proposed solvers are compared with the state-of-the-art ones on four real-world datasets with approx. 50000 image pairs in total.
  arXiv  Detail & Related papers  (2020-12-01T13:09:59Z)
• Pushing the Envelope of Rotation Averaging for Visual SLAM [69.7375052440794]
  We propose a novel optimization backbone for visual SLAM systems. We leverage averaging to improve the accuracy, efficiency and robustness of conventional monocular SLAM systems. Our approach can exhibit up to 10x faster with comparable accuracy against the state-art on public benchmarks.
  arXiv  Detail & Related papers  (2020-11-02T18:02:26Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.