Portable visual metrology without traditional self-calibration measurement model

Long, Changyu; Zhu, Jigui; Yi, Wei-Jian

doi:10.1016/j.measurement.2016.05.017

Cited by 8 publications

(3 citation statements)

References 13 publications

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“…Other than assuming nominal values for intrinsic parameters, precise camera calibration is required for precise measuring. Accurate camera calibration is necessary in photogrammetry systems and that is why continuous and recent improvements regarding mathematical analysis of the data taken for self-calibration [ 11 , 12 , 13 ] and image distortion correction [ 14 , 15 ] can be found in the literature. Nowadays there are several software applications for close range photogrammetry in industry using optical targets (i.e., Aicon 3D, Geodetic V-Stars, Creaform MaxShot3D, GOM Tritop, etc.)…”

Section: Camera Model Self-calibration For Precisionmentioning

confidence: 99%

“…Better accuracy was necessary for gaining performance when measuring raw parts larger than 1 m where the errors would increase proportionally to the size, as well as for applications where tighter raw material clearances may be expected. Indeed, camera calibration is a relevant uncertainty contributor in photogrammetry [ 2 , 10 , 11 ], and precise measurements require precise camera model calibration (so called intrinsic parameters). Continuous and recent improvements regarding the mathematical analysis of the data taken for calibration [ 11 , 12 , 13 ] and image distortion correction [ 14 , 15 ] can be found in the literature.…”

Section: Introductionmentioning

confidence: 99%

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Self-Calibrated In-Process Photogrammetry for Large Raw Part Measurement and Alignment before Machining

Mendikute

Yagüe‐Fabra

Zatarain

et al. 2017

Sensors

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Photogrammetry methods are being used more and more as a 3D technique for large scale metrology applications in industry. Optical targets are placed on an object and images are taken around it, where measuring traceability is provided by precise off-process pre-calibrated digital cameras and scale bars. According to the 2D target image coordinates, target 3D coordinates and camera views are jointly computed. One of the applications of photogrammetry is the measurement of raw part surfaces prior to its machining. For this application, post-process bundle adjustment has usually been adopted for computing the 3D scene. With that approach, a high computation time is observed, leading in practice to time consuming and user dependent iterative review and re-processing procedures until an adequate set of images is taken, limiting its potential for fast, easy-to-use, and precise measurements. In this paper, a new efficient procedure is presented for solving the bundle adjustment problem in portable photogrammetry. In-process bundle computing capability is demonstrated on a consumer grade desktop PC, enabling quasi real time 2D image and 3D scene computing. Additionally, a method for the self-calibration of camera and lens distortion has been integrated into the in-process approach due to its potential for highest precision when using low cost non-specialized digital cameras. Measurement traceability is set only by scale bars available in the measuring scene, avoiding the uncertainty contribution of off-process camera calibration procedures or the use of special purpose calibration artifacts. The developed self-calibrated in-process photogrammetry has been evaluated both in a pilot case scenario and in industrial scenarios for raw part measurement, showing a total in-process computing time typically below 1 s per image up to a maximum of 2 s during the last stages of the computed industrial scenes, along with a relative precision of 1/10,000 (e.g., 0.1 mm error in 1 m) with an error RMS below 0.2 pixels at image plane, ranging at the same performance reported for portable photogrammetry with precise off-process pre-calibrated cameras.

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Section: Camera Model Self-calibration For Precisionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Self-Calibrated In-Process Photogrammetry for Large Raw Part Measurement and Alignment before Machining

Mendikute

Yagüe‐Fabra

Zatarain

et al. 2017

Sensors

View full text Add to dashboard Cite

show abstract

“…Then, the real-time varying extrinsic parameters, which reflect the pose-position relationship between the camera and the world coordinate system, are calibrated by using different methods. For instance, if the measuring camera is carried by a highprecision controllable platform, then its extrinsic parameters can be gained directly [3], or else, the extrinsic parameters should be calculated by acquiring the pose-position relationship of the camera at different positions. On the basis of the intrinsic and extrinsic parameters, the relevant measurement work is completed according to the principle of videometrics.…”

Section: Introductionmentioning

confidence: 99%

A Real‐Time Deformation Monitoring Method for Large‐Scale Structure Based on Relay Camera

Liu

2021

Journal of Sensors

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In the process of the deformation monitoring for large-scale structure, the mobile vision method is often used. However, most of the existent researches rarely consider the real-time property and the variation of the intrinsic parameters. This paper proposes a real-time deformation monitoring method for the large-scale structure based on a relay camera. First, we achieve the real-time pose-position relationship by using the relay camera and the coded mark points whose coordinates are known. The real-time extrinsic parameters of the measuring camera are then solved according to the constraint relationship between the relay camera and the measuring camera. Second, the real-time intrinsic parameters of the measuring camera are calculated based on the real-time constraint relationship among the extrinsic parameters, the intrinsic parameters, and the fundamental matrix. Finally, the coordinates of the noncoded measured mark points, which are affixed to the surface of the structure, are achieved. Experimental results show that the accuracy of the proposed method is higher than 1.8 mm. Besides, the proposed method also possesses the real-time and automation property.

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Profile Calibration of Dynamically Measuring Rail Wear Using LIS

Wang

Liu

et al. 2018

Lecture Notes in Electrical Engineering

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Portable visual metrology without traditional self-calibration measurement model

Cited by 8 publications

References 13 publications

Self-Calibrated In-Process Photogrammetry for Large Raw Part Measurement and Alignment before Machining

Self-Calibrated In-Process Photogrammetry for Large Raw Part Measurement and Alignment before Machining

A Real‐Time Deformation Monitoring Method for Large‐Scale Structure Based on Relay Camera

Profile Calibration of Dynamically Measuring Rail Wear Using LIS

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