Analysis of Camera Calibration with Respect to Measurement Accuracy

Semeniuta, Oleksandr

doi:10.1016/j.procir.2015.12.108

Cited by 30 publications

(16 citation statements)

References 10 publications

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“…In this study, a visual system calibration method based on machine tool coordinate information feedback is proposed on the basis of the theory of image measuring and traditional camera calibration methods [ 25 , 26 , 27 , 28 ]. The parameters, such as cutter displacement coordinate and mark point coordinate for calibration, are obtained from position feedback of the numerical control system.…”

Section: Calibration Of Visual Tool-setting Systemmentioning

confidence: 99%

Computer Vision Tool-Setting System of Numerical Control Machine Tool

Hou

Zhang

Yang

2020

Sensors

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An automatic tool-setting and workpiece online detecting system was proposed to study the key technologies of next-generation intelligent vision computerized numerical control (CNC) machines. A computer vision automatic tool-setting system for a CNC machine was set up on the basis of the vision tool-setting principle. A rapid vision calibration method based on the position feedback from the CNC machine was proposed on the basis of the theory of traditional vision system calibration. The coordinate mapping relationship of the image and the CNC machine, the tool-setting mark point on the workpiece, and the tool tip were calibrated. The vision system performance testing and system calibration experiments were performed. Experimental results indicated that the time consumption was 128 ms in image processing. The precision of tool setting and measuring was less than 1 μm. The workpiece positioning and processing online detection function of the system can completely meet the requirements of visual CNC machine application, and the system has wide application prospects.

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Section: Calibration Of Visual Tool-setting Systemmentioning

confidence: 99%

Computer Vision Tool-Setting System of Numerical Control Machine Tool

Hou

Zhang

Yang

2020

Sensors

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“…Intrinsic calibration consists in finding these parameters. To do so, we should establish the correspondence between a set of 3D points and their projected 2D image points [Sem16].…”

Section: Camera's Intrinsic Parametersmentioning

confidence: 99%

Calibrating Low-cost Structured-light 3D Sensors

Chakib¹,

Mérillou²,

Vincent³

et al. 2018

WSCG 2018 - Full Papers Proceedings

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Consumer-grade RGB-D cameras are widely accessible, but they suffer from a lack of accuracy when compared to professional-grade 3D scanning solutions. In this paper, we propose a new method for calibrating an Intel RealSense SR300 camera, adaptable to other structured light sensors. The method uses classical checkerboard calibration and a coordinate-measuring machine (CMM) based setup with a calibrating plane. It delivers better results than the manufacturers settings.

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“…A sensible alternative can be to gather a relatively large set of images (or image pairs in the case of a stereo system) and evaluate how different subsets of the images work as an input to the standard calibration procedures. This approach has been investigated in a previous work by the author (Semeniuta, 2016), with an observation that the calibration parameters in a general form can be described by Gaussian distributions if numerous calibration runs with different subsets are invoked. However, it is challenging to select an optimal sample from such distribution if only one camera is used.…”

Section: Introductionmentioning

confidence: 99%

Subset-based stereo calibration method optimizing triangulation accuracy

Semeniuta¹

2021

PeerJ Computer Science

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Calibration of vision systems is essential for performing measurement in real world coordinates. For stereo vision, one performs stereo calibration, the results of which are used for 3D reconstruction of points imaged in the two cameras. A common and flexible technique for such calibration is based on collection and processing pairs of images of a planar chessboard calibration pattern. The inherent weakness of this approach lies in its reliance on the random nature of data collection, which might lead to better or worse calibration results, depending on the collected set of image pairs. In this paper, a subset-based approach to camera and stereo calibration, along with its implementation based on OpenCV, is presented. It utilizes a series of calibration runs based on randomly chosen subsets from the global set of image pairs, with subsequent evaluation of metrics based on triangulating the features in each image pair. The proposed method is evaluated on a collected set of chessboard image pairs obtained with two identical industrial cameras. To highlight the capabilities of the method to select the best-performing calibration parameters, a principal component analysis and clustering of the transformed data was performed, based on the set of metric measurements per each calibration run.

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Analysis of Camera Calibration with Respect to Measurement Accuracy

Cited by 30 publications

References 10 publications

Computer Vision Tool-Setting System of Numerical Control Machine Tool

Computer Vision Tool-Setting System of Numerical Control Machine Tool

Calibrating Low-cost Structured-light 3D Sensors

Subset-based stereo calibration method optimizing triangulation accuracy

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