• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.4
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• pp.349-356
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• 2016

This study investigates two camera self-calibration approaches, on-site self-calibration and laboratorial self-calibration, both of which are based on self-calibration theory and implemented by using a commercial photogrammetric solution, Agisoft PhotoScan. On-site self-calibration implements camera self-calibration and aerial triangulation by using the same aerial photos. Laboratorial self-calibration implements camera self-calibration by using photos captured onto a patterned target displayed on a digital panel, then conducts aerial triangulation by using the aerial photos. Aerial photos are captured by an unmanned aerial vehicle, and target photos are captured onto a 27in LCD monitor and a 47in LCD TV in two experiments. Calibration parameters are estimated by the two approaches and errors of aerial triangulation are analyzed. Results reveal that on-site self-calibration excels laboratorial self-calibration in terms of vertical accuracy. By contrast, laboratorial self-calibration obtains better horizontal accuracy if photos are captured at a greater distance from the target by using a larger display panel.

• Journal of Ocean Engineering and Technology
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• v.35 no.3
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• pp.183-190
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• 2021

Tomographic particle image velocimetry (PIV) is a widely used method that measures a three-dimensional (3D) flow field by reconstructing camera images into voxel images. In 3D measurements, the setting and calibration of the camera's mapping function significantly impact the obtained results. In this study, a camera self-calibration technique is applied to tomographic PIV to reduce the occurrence of errors arising from such functions. The measured 3D particles are superimposed on the image to create a disparity map. Camera self-calibration is performed by reflecting the error of the disparity map to the center value of the particles. Vortex ring synthetic images are generated and the developed algorithm is applied. The optimal result is obtained by applying self-calibration once when the center error is less than 1 pixel and by applying self-calibration 2-3 times when it was more than 1 pixel; the maximum recovery ratio is 96%. Further self-correlation did not improve the results. The algorithm is evaluated by performing an actual rotational flow experiment, and the optimal result was obtained when self-calibration was applied once, as shown in the virtual image result. Therefore, the developed algorithm is expected to be utilized for the performance improvement of 3D flow measurements.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.379-382
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• 2002

Among the CMM calibration techniques, the calibration with standard specimen is most accurate way to acquire the required precision. When there is no standard specimen, the calibration of CMM with itself is possible. This calibration method is called "self-calibration". In this paper, we developed self-calibration algorithm for CMM XY plane. It is possible to calculate the in-plane error and out-of-plane error of CMM with 3 different measurement of same artifact. Experimental result shows that the non-orthogonality error is dominant in in-plane error and the self-calibration result and laser interferometer measured result have almost same value.ame value.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.3
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• pp.18-27
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• 2010

In this paper, a 1.2V 7-bit 1GSPS A/D converter with offset self-calibration is proposed. The proposed A/D converter structure is based on the folding-interpolation whose folding rate is 2, interpolation rate is 8. Further, for the purpose of improving the chip performance, an offset self-calibration circuit is used. The offset self-calibration circuit reduce the variation of the offset-voltage，due to process mismatch, parasitic resistor, and parasitic capacitance. The chip has been fabricated with a 1.2V 65nm 1-poly 6-metal CMOS technology. The effective chip area is $0.87mm^2$ and the power dissipates about 110mW at 1.2V power supply. The measured SNDR is about 39.1dB when the input frequency is 250MHz at 800MHz sampling frequency. The measured SNDR is 3dB higher than the same circuit without any calibration.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.752-757
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• 2003

Recently, 3D structure recovery through self-calibration of camera has been actively researched. Traditional calibration algorithm requires known 3D coordinates of the control points while self-calibration only requires the corresponding points of images, thus it has more flexibility in real application. In general, self-calibration algorithm results in the nonlinear optimization problem using constraints from the intrinsic parameters of the camera. Thus, it requires initial value for the nonlinear minimization. Traditional approaches get the initial values assuming they have the same intrinsic parameters while they are dealing with the situation where the intrinsic parameters of the camera may change. In this paper, we propose new initialization method using the minimum 2 images. Proposed method is based on the assumption that the least violation of the camera’s intrinsic parameter gives more stable initial value. Synthetic and real experiment shows this result.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4C
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• pp.400-406
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• 2006

Knowledge of camera parameters, such as position, orientation and focal length, is essential to 3D information recovery or virtual object insertion. This paper analyzes the error sensitivity of focal length due to position error of feature points which are employed for self-calibration. We verify the dependency of the focal length on the distance from the principal point to feature points with simulations, and propose a criterion for feature selection to reduce the error sensitivity.

• Journal of Information Technology Applications and Management
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• v.25 no.2
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• pp.41-52
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• 2018

This paper presents a method for accurate camera self-calibration based on SIFT Feature Detection and image quality assessment. We performed image quality assessment to select high quality images for the camera self-calibration process. We defined high quality images as those that contain little or no blur, and have maximum contrast among images captured within a short period. The image quality assessment includes blur detection and contrast assessment. Blur detection is based on the statistical analysis of energy and standard deviation of high frequency components of the images using Discrete Cosine Transform. Contrast assessment is based on contrast measurement and selection of the high contrast images among some images captured in a short period. Experimental results show little or no distortion in the perspective view of the images. Thus, the suggested method achieves camera self-calibration accuracy of approximately 93%.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.391-394
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• 2005

In this paper, we present an approach that is able to reconstruct 3 dimensional metric models from un-calibrated images acquired by a freely moved camera system. If nothing is known of the calibration of either camera, nor the arrangement of one camera which respect to the other, then the projective reconstruction will have projective distortion which expressed by an arbitrary projective transformation. The distortion on the reconstruction is removed from projection to metric through self-calibration. The self-calibration requires no information about the camera matrices, or information about the scene geometry. Self-calibration is the process of determining internal camera parameters directly from multiply un-calibrated images. Self-calibration avoids the onerous task of calibrating cameras which needs to use special calibration objects. The root of the method is setting a uniquely fixed conic(absolute quadric) in 3D space. And it can make possible to figure out some way from the images. Once absolute quadric is identified, the metric geometry can be computed. We compared reconstruction image from calibrated images with the result by self-calibration method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.10a
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• pp.345-346
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• 2006

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_1
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• pp.511-518
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• 2012

It is well-known that non-metric digital cameras have to be calibrated for the close-range photogrammetry. But, the self-calibration is still not an easy task because it requires rather a large calibration site of accurate control points, multiple image acquisitions in different positions, and accurate image point measurements that are quite labor-intensive and time-consuming. Based on the premise, this study carried out check point accuracy analysis from self-calibration of different control point designs and photo combinations. The test results showed that the calibration using three photos covering three-dimensional control points produced high accuracy, but control points on a plane could attain the comparable accuracy with four photos including a 90-degree rotated photo. We then compared the target accuracy of on-site self-calibration using flat control points to that of laboratory-self calibration and observed comparable results.