Which pattern? Biasing aspects of planar calibration patterns and detection methods

Mallon, John; Whelan, Paul F.

doi:10.1016/j.patrec.2006.12.008

Cited by 99 publications

(57 citation statements)

References 17 publications

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“…In order to calculate image coordinates pi,j,k for each marker, we have implemented in MATLAB the image processing algorithms for detection of dot and chessboard pattern from [30]. All automatically processed images of calibration and test sequences have been checked manually afterwards to delete points in low-illuminated areas, around glare, etc.…”

Section: Equipmentmentioning

confidence: 99%

Optimal calibration of a prism-based videoendoscopic system for precise 3D measurements

Gorevoy¹,

Мачихин²

2017

Computer Optics

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Modern videoendoscopes are capable of performing precise three-dimensional (3D) measurements of hard-to-reach elements. An attachable prism-based stereo adapter allows one to register images from two different viewpoints using a single sensor and apply stereoscopic methods. The key condition for achieving high measurement accuracy is the optimal choice of a mathematical model for calibration and 3D reconstruction procedures. In this paper, the conventional pinhole camera models with polynomial distortion approximation were analyzed and compared to the ray tracing model based on the vector form of Snell's law. We, first, conducted a series of experiments using an industrial videoendoscope and utilized the criteria based on the measurement error of a segment length to evaluate the mathematical models considered. The experimental results confirmed a theoretical conclusion that the ray tracing model outperforms the pinhole models in a wide range of working distances. The results may be useful for the development of new stereoscopic measurement tools and algorithms for remote visual inspection in industrial and medical applications.Keywords: remote visual inspection, 3D spatial measurements, camera calibration, distortion model, prism distortion.Citation: Gorevoy AV, Machikhin AS. Optimal calibration of a prism-based videoendoscopic system for precise 3D measurements.

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Section: Equipmentmentioning

confidence: 99%

Optimal calibration of a prism-based videoendoscopic system for precise 3D measurements

Gorevoy¹,

Мачихин²

2017

Computer Optics

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“…The robustness of the control point detection under these two transformations is based on the combination of the pattern employed and on the detection method used. Therefore, there are two possible sources of bias in control point recovery which are named according to Mallon and Whealan [9]: perspective bias and distortion bias. The main goal would be to obtain bias free data, as this is clearly necessary for obtaining unbiased estimates for calibration algorithms.…”

Section: Introductionmentioning

confidence: 99%

“…However, it is not always the case. The bias does not have the same magnitude for all types of patterns: for example, Mallon and Whealan [9] show that detected control points obtained by using centroid recovery principle can potentially be corrupted by both perspective bias and distortion bias, with the likelihood of larger distortion bias magnitude in a typical camera. They also show that the compensation of distortion bias from such circular pattern points is not possible without knowing the distortion field.…”

Section: Introductionmentioning

confidence: 99%

Camera Matrix Calibration Using Circular Control Points and Separate Correction of the Geometric Distortion Field

Rudakova¹,

Monasse²

2014

2014 Canadian Conference on Computer and Robot Vision

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To cite this version:Victoria Rudakova, Pascal Monasse. Camera matrix calibration using circular control points and separate correction of the geometric distortion field. IEEE. Abstract-We achieve a precise camera calibration using circular control points by, first, separation of the lens distortion parameters from other camera parameters and computation of the distortion field in advance by using a calibration harp. Second, in order to compensate for perspective bias, which is prone to occur when using a circled pattern, we incorporate conic affine transformation into the minimization error when estimating the homography, and leave all the other calibration steps as they are used in the literature. Such an error function allows to compensate for the perspective bias. Combined with precise keypoint detection, the approach is shown to be more stable than current state-of-the-art global calibration method.

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“…The input requirements of planar approaches simply involve imaging a planar target. Planar calibration targets such as a chessboard or circular dot patterns are commonly used to specify the planar feature points [8]. The stability of these planar calibration methods has been well studied in the literature.…”

Section: Introductionmentioning

confidence: 99%

Capturing Optimal Image Networks for Planar Camera Calibration

Byrne

Mallon

Whelan

2011

2011 Irish Machine Vision and Image Processing Conference

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Abstract-This paper details a novel approach to specifying the optimal pose of planar targets in camera calibration that both reduces the number of images required, and improves the parameter estimates. This is accomplished within a semisupervised strategy where virtual images of planar calibration targets are generated and displayed. These virtual targets are then replicated by the user to generate an image network with optimal geometry for the recovery of the camera parameters. Optimal planar pose is specified by enforcing maximum independence within the calibration constraints offered by each image within the network. This solution space is further refined to ensure that the generated target pose is suitable for easy acquisition and subsequent feature extraction processes. The results on simulated and real data demonstrate that proper consideration of image network geometry directly leads to more accurate camera parameter estimates.

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Which pattern? Biasing aspects of planar calibration patterns and detection methods

Cited by 99 publications

References 17 publications

Optimal calibration of a prism-based videoendoscopic system for precise 3D measurements

Optimal calibration of a prism-based videoendoscopic system for precise 3D measurements

Camera Matrix Calibration Using Circular Control Points and Separate Correction of the Geometric Distortion Field

Capturing Optimal Image Networks for Planar Camera Calibration

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