• 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.

• 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.

• 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.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2689-2708
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• 2016

Multi-camera systems which integrate two or more low-cost digital cameras are adopted to reach higher ground coverage and improve the base-height ratio in low altitude remote sensing. To guarantee accurate multi-camera integration, the geometric relationship among cameras must be determined through platform calibration techniques. This paper proposed a combined two-step platform calibration method. In the first step, the static platform calibration was conducted based on the stable relative orientation constraint and convergent conditions among cameras in static environments. In the second step, a dynamic platform self-calibration approach was proposed based on not only tie points but also straight lines in order to correct the small change of the relative relationship among cameras during dynamic flight. Experiments based on the proposed two-step platform calibration method were carried out with terrestrial and aerial images from a multi-camera system combined with four consumer-grade digital cameras onboard an unmanned aerial vehicle. The experimental results have shown that the proposed platform calibration approach is able to compensate the varied relative relationship during flight, acquiring the mosaicing accuracy of virtual images smaller than 0.5pixel. The proposed approach can be extended for calibrating other low-cost multi-camera system without rigorously mechanical structure.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.3
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• pp.281-288
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• 2006

Recent increase in the number of pixels of a non-metric digital camera encourages to use it for close-range photogrammetry such as modeling cultural asset and buildings. However, these cameras have to be calibrated far close-range photogrammetry application. For self-calibration, an appropriate pbotograrnmetric network and object field should be designed. In this paper, we studied the effect on self-calibration accuracy changes according to the change of the number of ground control points, dimensions of the ground control points, and the combination of images. We concluded that self-calibration with three photos including a vertical photo can give the stable accuracy of interior orientation parameters and 10 ground control points on a plane can give high accuracy for object reconstruction.

• 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.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.6
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• pp.475-483
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• 2015

This study examined the feasibility of using an automatic lens distortion correction (ALDC) camera as the payload for a photogrammetric unmanned aerial vehicle (UAV) system. First, lens distortion for the interior orientation (IO) parameters was estimated. Although previous studies have largely ignored decentering distortion, this study revealed that more than 50% of the distortion of the ALDC camera was caused by decentering distortion. Second, we compared the accuracy of bundle adjustment for camera calibration using three image types: raw imagery without the ALDC option; imagery corrected using lens profiles; and imagery with the ALDC option. The results of image triangulation, the digital terrain model (DTM), and the orthoimage using the IO parameters for the ALDC camera were similar to or slightly better than the results using self-calibration. These results confirm that the ALDC camera can be used in a photogrammetric UAV system using only self-calibration.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.779-782
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• 2010

Self-calibration에서 3차원 좌표의 복원은 호모그래피 행렬 H를 계산하면 얻을 수 있다. 이 호모그래피 행렬을 얻는 방법은 dual absolute quadric, Kruppa Equation(dual conic), plane at infinity(modulus constraint)를 사용하는 방법과 같이 세 가지 방법이 일반적으로 사용된다. 제안하는 방식은 dual absolute quadric을 사용한다. 카메라 내부 속성이 모든 뷰에서 동일하고 비틀림이나 영상의 원점이 중심이라는 가정을 두고 호모그래피 행렬 H를 계산한다. 실험을 통해서 주어진 가정으로 정밀한 복원이 가능함을 보였다.