Estimation of stereo and motion parameters using a variational principle

In many industrial sectors, Non Destructive Testing (NDT) methods are used for the thermomechanical analysis of parts in assemblies of engines or reactors or for the control of metal forming processes. This article suggests an automated multi-view approach for the thermal D 3 reconstruction required in order to compute D 3 surface temperature models. This approach is based only on infrared cameras mounted on a Cartesian robot. The low resolution of these cameras associated to a lack of texture to infrared images require to use a global approach based first on an uncalibrated rectification and then on the simultaneous execution, in a single step, of the dense D 3 reconstruction and of an extended self-calibration. The uncalibrated rectification is based on an optimization process under constraints which calculates the homographies without prior calculation of the Fundamental Matrix and which minimizes the projective deformations between the initial images and the rectified ones. The extended self-calibration estimates both the parameters of virtual cameras that could provide the rectified images directly, and the parameters of the robot. It is based on two criteria evaluated according to the noise level of the infrared images. This global approach is validated through the reconstruction of a hot object against a reference reconstruction acquired by a D 3 scanner.

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“…(5). The distortions are then corrected by applying symmetrical [26,27] or independent [28][29][30][31][32]…”

Section: Computation Of Homographiesmentioning

confidence: 99%

Automated thermal 3D reconstruction based on a robot equipped with uncalibrated infrared stereovision cameras

Sentenac

Bugarin

Ducarouge

et al. 2018

Advanced Engineering Informatics

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“…The Trivedi-Simplex algorithm [5] attempts to recover epi-polar geometry (3 rotation and 3 translation minus one scaling factor) by minimising the epi-polar errors of matched corners on the image plane. This is achieved by comparing the suggested epi-polar solution to all known matches using a robust M-Estimator [7] which accounts for the expected accuracy of the corner features in order to minimise contamination with outlier data, thus;…”

Section: Trivedi-simplexmentioning

confidence: 99%

An Evaluation of the Performance of RANSAC Algorithmsfor Stereo Camera Calibrarion

Lacey

Pinitkarn²,

Thacker³

2000

Procedings of the British Machine Vision Conference 2000

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This paper compares the use of RANSAC for the determination of epipolar geometry for calibrated stereo reconstruction of 3D data with more conventional optimisation schemes. The paper illustrates the poor convergence efficiency of RANSAC which is explained by a theoretical relationship describing its dependency upon the number of model parameters. The need for an a-priori estimate of outlier contamination proportion is also highlighted. A new algorithm is suggested which attempts to make better use of the solutions found during the RANSAC search while giving a convergence criteria which is independent of outlier proportion. Although no significant benefit can be found for the use of RANSAC on the problem of stereo camera calibration estimation. The new algorithm suggests a simple way of improving the efficiency of RANSAC searches which we believe would be of value in a wide range of machine vision problems.

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“…As the object is measured in an arbitrary co-ordinate frame the parameters describing the absolute transformation are redundant and only those relevant to the stereo camera system s are required. For calibrating from image correspondences the X 2 is formulated following the numerical method of Trivedi [7]. The method can accommodate correspondance data either from matched epi-polar tangencies [3] or matched corners [8].…”

Section: Fixed Stereo Camera Calibrationmentioning

confidence: 99%

Online Calibration of a 4 DOF Stereo Head

Thacker¹,

Courtney²

1992

Procedings of the British Machine Vision Conference 1992

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This paper addresses the problem of recovering accurate 3D geometry from a 4 degree of freedom stereo robot head. We argue that successful implementation of stereo vision in a real world application will require a self tuning system. This paper describes a statistical framework for the combination of many sources of information for the calibration of a stereo camera system which would allow continual recalibration during normal use of the cameras. The calibration is maintained using modules at three levels: fixed verge, variable verge and pan/tilt/verge calibration. Together these modules provide the means to fuse data obtained at various head positions into a single coordinate frame.

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Estimation of stereo and motion parameters using a variational principle

Cited by 18 publications

References 6 publications

Automated thermal 3D reconstruction based on a robot equipped with uncalibrated infrared stereovision cameras

Automated thermal 3D reconstruction based on a robot equipped with uncalibrated infrared stereovision cameras

An Evaluation of the Performance of RANSAC Algorithmsfor Stereo Camera Calibrarion

Online Calibration of a 4 DOF Stereo Head

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