Automatic camera and range sensor calibration using a single shot

Geiger, Andreas; Moosmann, Frank; Car, Omer; Schuster, Bernhard

doi:10.1109/icra.2012.6224570

Cited by 512 publications

(419 citation statements)

References 18 publications

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“…To determine the image points of the checkerboard corners in each image with subpixel-accuracy, we use a well-known detection algorithm by Geiger et al (2012). Since we know the position of every checkerboard corner in the motion capture reference frame, we are able to compute the extrinsics of the camera in the reference frame based on 2D-3D correspondences by using OPnP (Zheng et al, 2013).…”

Section: Isprs Annals Of the Photogrammetry Remote Sensing And Spatimentioning

confidence: 99%

UCalMiCeL – UNIFIED INTRINSIC AND EXTRINSIC CALIBRATION OF A MULTI-CAMERA-SYSTEM AND A LASERSCANNER

Hillemann

Jutzi²

2017

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Unmanned Aerial Vehicle (UAV) with adequate sensors enable new applications in the scope between expensive, large-scale, aircraftcarried remote sensing and time-consuming, small-scale, terrestrial surveyings. To perform these applications, cameras and laserscanners are a good sensor combination, due to their complementary properties. To exploit this sensor combination the intrinsics and relative poses of the individual cameras and the relative poses of the cameras and the laserscanners have to be known. In this manuscript, we present a calibration methodology for the Unified Intrinsic and Extrinsic Calibration of a Multi-Camera-System and a Laserscanner (UCalMiCeL). The innovation of this methodology, which is an extension to the calibration of a single camera to a line laserscanner, is an unifying bundle adjustment step to ensure an optimal calibration of the entire sensor system. We use generic camera models, including pinhole, omnidirectional and fisheye cameras. For our approach, the laserscanner and each camera have to share a joint field of view, whereas the fields of view of the individual cameras may be disjoint. The calibration approach is tested with a sensor system consisting of two fisheye cameras and a line laserscanner with a range measuring accuracy of 30mm. We evaluate the estimated relative poses between the cameras quantitatively by using an additional calibration approach for Multi-Camera-Systems based on control points which are accurately measured by a motion capture system. In the experiments, our novel calibration method achieves a relative pose estimation with a deviation below 1.8• and 6.4mm.

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Section: Isprs Annals Of the Photogrammetry Remote Sensing And Spatimentioning

confidence: 99%

UCalMiCeL – UNIFIED INTRINSIC AND EXTRINSIC CALIBRATION OF A MULTI-CAMERA-SYSTEM AND A LASERSCANNER

Hillemann

Jutzi²

2017

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…8. Evaluation of the registering algorithm emulating the camera setup presented in [11]. Rotation (left) and translation (right) error is shown with varying degrees of Gaussian noise present in both the image and the point cloud.…”

Section: B Point-to-line Icp Registrationmentioning

confidence: 99%

“…fitting presented in [11]. Their evaluation consists of the rotation error e r -distance between computed and ground truth translation vectors-and translation error e t -angle between computed and ground truth rotation axis-with different Kinect/camera setups.…”

Section: B Point-to-line Icp Registrationmentioning

confidence: 99%

“…The detection approach is similar to [13], without constraining the point cloud to: a) an RGBD image [13], b) a special pattern [11] or c) for the scene to have certain geometrical features [3].…”

Section: Introductionmentioning

confidence: 99%

“…For the registration of several images to a point cloud [7], some algorithms start from an initial 3D reconstruction from the images by Structure-fromMotion (SfM) [8], [9], [10]. Registration algorithms for multihead sensors -for example, Kinect and RGB camera-using calibration patterns have also been presented [11].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Registration of images to unorganized 3D point clouds using contour cues

Pujol-Miro

Ruiz-Hidalgo

Casas

2017

2017 25th European Signal Processing Conference (EUSIPCO)

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Abstract-Low resolution commercial 3D sensors contribute to computer vision tasks even better when the analysis is carried out in a combination with higher resolution image data. This requires registration of 2D images to unorganized 3D point clouds. In this paper we present a framework for 2D-3D data fusion to obtain directly the camera pose of a 2D color image in relation to a 3D point cloud. It includes a novel multiscale intensity feature detection algorithm and a modified ICP procedure based on point-to-line distances. The framework is generic for several data types (such as CAD designs or LiDAR data without photometric information), and results show that performance is comparable to the state of the art, while avoiding manual markers or specific patterns on the data.

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Modeling and validation of three‐dimensional sliding‐rocking rigid block subjected to earthquake excitation

Bao

2022

Earthq Engng Struct Dyn

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A freestanding rigid block subjected to earthquake excitation is a problem of significant interest to the earthquake engineering community because it has many direct applications in the seismic performance evaluation of both structural and non‐structural components. Previous studies on this classical problem usually assume planar rocking is the only motion that can be activated. However, this is clearly not true when friction coefficient is not sufficiently large or the earthquake excitation is bi‐directional. To address this knowledge gap, this paper presents a three‐dimensional sliding‐rocking rigid body model suitable for dynamic analysis. Important aspects for this model, which include the formulation of nonlinear equations of motion, transitional criteria for different motion modes, as well as the approach to handle the impact, are described. Validation of the proposed model consists of two parts. The first part is the comparison with the numerical prediction from a different model available in the literature. The second part is the comparison with the experimental study from a series of shake table tests using vision‐based measurement. These comparisons suggest the proposed model provide relatively good accuracy. Finally, a case study of overturning probability of a non‐structural component shows that using a three‐dimensional modeling approach can give substantially different result compared to a two‐dimensional rocking model, which highlights the necessity of adopting such model.

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Automatic camera and range sensor calibration using a single shot

Cited by 512 publications

References 18 publications

UCalMiCeL – UNIFIED INTRINSIC AND EXTRINSIC CALIBRATION OF A MULTI-CAMERA-SYSTEM AND A LASERSCANNER

UCalMiCeL – UNIFIED INTRINSIC AND EXTRINSIC CALIBRATION OF A MULTI-CAMERA-SYSTEM AND A LASERSCANNER

Registration of images to unorganized 3D point clouds using contour cues

Modeling and validation of three‐dimensional sliding‐rocking rigid block subjected to earthquake excitation

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