AC/DCC : Accurate Calibration of Dynamic Camera Clusters for Visual SLAM

Rebello, Jason; Fung, Angus; Waslander, Steven L.

doi:10.1109/icra40945.2020.9197217

Cited by 3 publications

(3 citation statements)

References 19 publications

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“…In all the above cases, care has to be taken to place the targets within the FOV of the sensors to ensure sufficient scan points have contacted the targets, and the target is fully visible in the camera. This limits the possible sensor configurations to those with sufficient overlap, and calibration results may degrade as overlap becomes smaller due to a reduced measurement sample space [10].…”

Section: Related Workmentioning

confidence: 99%

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A Target-Based Extrinsic Calibration Framework for Non-Overlapping Camera-Lidar Systems Using a Motion Capture System

Charron¹,

Waslander²,

Narasimhan³

2023

Preprint

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In this work, we present a novel target-based lidar-camera extrinsic calibration methodology that can be used for non-overlapping field of view (FOV) sensors. Contrary to previous work, our methodology overcomes the nonoverlapping FOV challenge using a motion capture system (MCS) instead of traditional simultaneous localization and mapping approaches. Due to the high relative precision of MCSs, our methodology can achieve both the high accuracy and repeatable calibrations of traditional target-based methods, regardless of the amount of overlap in the sensors' field of view. We show using simulation that we can accurately recover extrinsic calibrations for a range of perturbations to the true calibration that would be expected in real circumstances. We also validate that high accuracy calibrations can be achieved on experimental data. Furthermore, We implement the described approach in an extensible way that allows any camera model, target shape, or feature extraction methodology to be used within our framework. We validate this implementation on two target shapes: an easy to construct cylinder target and a diamond target with a checkerboard. The cylinder target shape results show that our methodology can be used for degenerate target shapes where target poses cannot be fully constrained from a single observation, and distinct repeatable features need not be detected on the target.

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Section: Related Workmentioning

confidence: 99%

“…This approach can lead to compounding of calibration errors along the chain. The accuracy of the calibration also depends on the amount of overlap between sensors since the measurement sample space is restricted to lie within the overlapping region [10].…”

Section: Introductionmentioning

confidence: 99%

A Target-Based Extrinsic Calibration Framework for Non-Overlapping Camera-Lidar Systems Using a Motion Capture System

Charron¹,

Waslander²,

Narasimhan³

2023

Preprint

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“…They adopted the next-best-view strategy in information theoretic to select calibration measurement to reduce the parameter uncertainty. Furthermore, they [17] improved DCC calibration accuracy by collecting measurements over the entire configuration space of the 3-DOF gimbal and a pose-loop error optimization algorithm. The relative orientation may sometimes be performed when the rotating actuate mechanism and the camera are seperate.…”

Section: Introductionmentioning

confidence: 99%

Geometric Calibration of Rotational Vision System for Dynamic Exterior Orientation

Qiu

Zhang

Xiong

et al. 2021

Preprint

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Rotational vision system (RVS) is a common type of active vision with only rotational freedom. Typically, the rotational freedom is provided by turntable and pan-tilt-zoom (PTZ). Or eye in hand (EIH) structure in an articulated arm robot. The ideal assumption that rotation axes are perfectly aligned with the coordinate axes of the local camera is mostly violated due to assembling deviations and limitations of manufacturing accuracy. To solve this problem, we propose a generalized deviation model for a specified rotation axis that relates the rotation motion of the platform to the exterior orientation (EO) of the camera. Based on it we put heuristic estimation algorithms through minimizing global reprojection error and fitting a circle in space respectively for rotating platform with or without accurate angle measurements with constrained global optimization. Implemented experiments on a servo pan-tilt turntable validate the accuracy and efficiency of the above models and calibration technique.

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DC-VINS: Dynamic Camera Visual Inertial Navigation System with Online Calibration

Rebello

Waslander

2021

2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)

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AC/DCC : Accurate Calibration of Dynamic Camera Clusters for Visual SLAM

Cited by 3 publications

References 19 publications

A Target-Based Extrinsic Calibration Framework for Non-Overlapping Camera-Lidar Systems Using a Motion Capture System

A Target-Based Extrinsic Calibration Framework for Non-Overlapping Camera-Lidar Systems Using a Motion Capture System

Geometric Calibration of Rotational Vision System for Dynamic Exterior Orientation

DC-VINS: Dynamic Camera Visual Inertial Navigation System with Online Calibration

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