Modelling and calibration of depth-dependent distortion for large depth visual measurement cameras

Sun, Peng; Lü, Naiguang; Dong, Mingli

doi:10.1364/oe.25.009834

Cited by 17 publications

(6 citation statements)

References 9 publications

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“…This is almost 3 times bigger than that between the Red and NIR bands (52.6 μm and 53.9 μm respectively). The maximum radial distortion is confirmed by similar studies on conventional (RGB) consumer-grade cameras (Fraser and Shortis, 1990;Remondino and Fraser, 2006;Moe et al, 2010;Sun et al, 2017). Finally, the correlation matrices should be analysed.…”

Section: Results Analysis and Discussionmentioning

confidence: 58%

Preliminary Investigation Into the Geometric Calibration of the Micasense Rededge-M Multispectral Camera

Frontera

Smith

Marsh

2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Multispectral cameras, in the past the prerogative of Remote Sensing (RS) applications via satellites and manned aircraft, are becoming increasingly used in photogrammetric applications. Moreover, the ubiquitous use of Unmanned Aerial Vehicles (UAVs) has created a need for the miniaturisation of sensors, which has contributed to the availability of a wide range of relatively low-cost and lightweight cameras. Therefore, small multispectral cameras mounted on UAVs provide an effective and low-cost solution when it comes to acquiring airborne radiometric data.With the growing interest for such sensors to perform photogrammetric tasks, camera calibration remains an essential step in order to obtain reliable and geometrically accurate information.This paper will investigate the camera calibration parameters between the five bands of the MicaSense RedEdge-M sensor from laboratory trials. The results of the camera calibration will be obtained from the use, primarily, of Australis software and a calibration frame within the Nottingham Geospatial Institute. The variations of the parameters demonstrate the need for distortion correction separately within each band before using the images for photogrammetry.

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Section: Results Analysis and Discussionmentioning

confidence: 58%

Preliminary Investigation Into the Geometric Calibration of the Micasense Rededge-M Multispectral Camera

Frontera

Smith

Marsh

2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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show abstract

“…In the rest of this section, we arranged two different scenes to complete the accuracy assessment: scene A, with a general object, was used to show the general applicability of the proposed method compared to the standard robot–world and hand–eye calibration approaches, and scene B, a photogrammetric retro-reflective target was used to improve the feature point-locating accuracy and decrease the false match rate for calibrating the extrinsic camera. Before the experiment, we used [ 32 ] to calibrate the camera together with seven parameters of lens, so the images were undistorted prior to being further used in order to improve sparse bundle adjustment results.…”

Section: Methodsmentioning

confidence: 99%

Simultaneous Robot–World and Hand–Eye Calibration without a Calibration Object

Dong

Lü

et al. 2018

Sensors

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An extended robot–world and hand–eye calibration method is proposed in this paper to evaluate the transformation relationship between the camera and robot device. This approach could be performed for mobile or medical robotics applications, where precise, expensive, or unsterile calibration objects, or enough movement space, cannot be made available at the work site. Firstly, a mathematical model is established to formulate the robot-gripper-to-camera rigid transformation and robot-base-to-world rigid transformation using the Kronecker product. Subsequently, a sparse bundle adjustment is introduced for the optimization of robot–world and hand–eye calibration, as well as reconstruction results. Finally, a validation experiment including two kinds of real data sets is designed to demonstrate the effectiveness and accuracy of the proposed approach. The translation relative error of rigid transformation is less than 8/10,000 by a Denso robot in a movement range of 1.3 m × 1.3 m × 1.2 m. The distance measurement mean error after three-dimensional reconstruction is 0.13 mm.

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“…The length between the two RRTs is measured or calibrated by instruments with high (several micrometer) accuracy. One of the measurement instruments is composed by an interferometer, a microscope and a granite rail [ 25 , 26 ]. Generally, a scale bar performs in photogrammetry as a metric for true scale, especially in multi-image offline systems.…”

Section: Methodsmentioning

confidence: 99%

Simultaneous All-Parameters Calibration and Assessment of a Stereo Camera Pair Using a Scale Bar

Sun

Lü

Dong

et al. 2018

Sensors

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Highly accurate and easy-to-operate calibration (to determine the interior and distortion parameters) and orientation (to determine the exterior parameters) methods for cameras in large volume is a very important topic for expanding the application scope of 3D vision and photogrammetry techniques. This paper proposes a method for simultaneously calibrating, orienting and assessing multi-camera 3D measurement systems in large measurement volume scenarios. The primary idea is building 3D point and length arrays by moving a scale bar in the measurement volume and then conducting a self-calibrating bundle adjustment that involves all the image points and lengths of both cameras. Relative exterior parameters between the camera pair are estimated by the five point relative orientation method. The interior, distortion parameters of each camera and the relative exterior parameters are optimized through bundle adjustment of the network geometry that is strengthened through applying the distance constraints. This method provides both internal precision and external accuracy assessment of the calibration performance. Simulations and real data experiments are designed and conducted to validate the effectivity of the method and analyze its performance under different network geometries. The RMSE of length measurement is less than 0.25 mm and the relative precision is higher than 1/25,000 for a two camera system calibrated by the proposed method in a volume of 12 m × 8 m × 4 m. Compared with the state-of-the-art point array self-calibrating bundle adjustment method, the proposed method is easier to operate and can significantly reduce systematic errors caused by wrong scaling.

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Modelling and calibration of depth-dependent distortion for large depth visual measurement cameras

Cited by 17 publications

References 9 publications

Preliminary Investigation Into the Geometric Calibration of the Micasense Rededge-M Multispectral Camera

Preliminary Investigation Into the Geometric Calibration of the Micasense Rededge-M Multispectral Camera

Simultaneous Robot–World and Hand–Eye Calibration without a Calibration Object

Simultaneous All-Parameters Calibration and Assessment of a Stereo Camera Pair Using a Scale Bar

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