• 한국해양공학회지
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• 제35권3호
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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.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2005년도 추계종합학술대회
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.1248-1250
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• 1996

The objective of camera calibration is to obtain the correlation between camera image coordinate and 3-D real world coordinate. Most calibration methods are based on the camera model which consists of physical parameters of the camera like position, orientation, focal length, etc and in this case camera calibration means the process of computing those parameters. In this research, we suggest a new approach which must be very efficient because the artificial neural network(ANN) model implicitly contains all the physical parameters, some of which are very difficult to be estimated by the existing calibration methods. Implicit camera calibration which means the process of calibrating a camera without explicitly computing its physical parameters can be used for both 3-D measurement and generation of image coordinates. As training each calibration points having different height, we can find the perspective projection point. The point can be used for reconstruction 3-D real world coordinate having arbitrary height and image coordinate of arbitrary 3-D real world coordinate. Experimental comparison of our method with well-known Tsai's 2 stage method is made to verify the effectiveness of the proposed method.

• 한국태양에너지학회 논문집
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• 제38권6호
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• pp.65-72
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• 2018

Since data-driven building technologies have been widely applied to building energy systems, the accuracy of building sensors has more impacts on the building performance and system performance analysis. Various building sensors, however, can have typical errors including a random error (noise) and a systematic error (bias). The systematic error is indicated by the difference between the mean of measurements and their true value. It may occur due to the sensor's physical condition, measured phenomena, working environments inside the systems. Unfortunately, a conventional calibration method has limitations in calibrating the systematic errors because of the difference between working environments and calibration conditions. In such situations, a novel sensor calibration method is needed to handle various sensor errors, especially for systematic errors, in building energy systems having various thermodynamic environments. This study proposes a building sensor calibration method named Virtual In-situ Calibration (VIC) and shows how it is applied into a real building system and how it solves the sensor errors.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.304-307
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• 1993

In this paper, we formulate Kalman filter for calibration of strapdown inertial measurment unit(SDIMU) on navigation system level and analyize its performance by covariance simulation method. It has been shown that the calibration method suggested in this paper is not largely influenced by accuracy of a mounting axis alignment required in calibration of SDIMU on IMU level.

• Ocean and Polar Research
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• 제33권2호
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• pp.171-183
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• 2011

Despite technological developments and application advances of Acoustic Doppler Current Profilers (ADCPs), no standard procedure has been adopted or accepted for calibration of ADCPs. Limitations of existing facilities for calibrating ADCPs, the complexity of ADCP instruments, and rapid changes in ADCP technology are some of the reasons why a standard procedure has not been adopted. However, there is increasing realization of the need for effective Quality Assurance (QA) and as part of that the importance of standardized calibration. In this study, the significance of calibration and QA plans for ADCPs is discussed and the calibration facilities for ADCPs at home and abroad are reported. Furthermore, the method for calibrating ADCPs using a towed car and its limitations are discussed. This study contributes to discussions surrounding the establishment of standard procedures for calibrating ADCPs and QA plans, and the construction of calibration facilities in the future.

• Journal of information and communication convergence engineering
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• 제12권4호
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• pp.208-214
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• 2014

In this paper, in order to solve the problems of a narrow viewing angle and the flip effect in a three-dimensional (3D) integral imaging display, we propose an improved system by using an eye tracking method based on the Kinect sensor. In the proposed method, we introduce two types of calibration processes. First process is to perform the calibration between two cameras within Kinect sensor to collect specific 3D information. Second process is to use a space calibration for the coordinate conversion between the Kinect sensor and the coordinate system of the display panel. Our calibration processes can provide the improved performance of estimation for 3D position of the observer's eyes and generate elemental images in real-time speed based on the estimated position. To show the usefulness of the proposed method, we implement an integral imaging display system using the eye tracking process based on our calibration processes and carry out the preliminary experiments by measuring the viewing angle and flipping effect for the reconstructed 3D images. The experimental results reveal that the proposed method extended the viewing angles and removed the flipping images compared with the conventional system.

• 한국측량학회지
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• 제33권3호
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• pp.211-218
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• 2015

The analysis of remote sensing data depends on sensor specifications that provide accurate and consistent measurements. However, it is not easy to establish confidence and consistency in data that are analyzed by different sensors using various radiometric scales. For this reason, the cross-calibration method is used to calibrate remote sensing data with reference image data. In this study, we used an airborne hyperspectral image in order to calibrate a multispectral image. We presented an automatic cross-calibration method to calibrate a multispectral image using hyperspectral data and spectral mixture analysis. The spectral characteristics of the multispectral image were adjusted by linear regression analysis. Optimal endmember sets between two images were estimated by spectral mixture analysis for the linear regression analysis, and bands of hyperspectral image were aggregated based on the spectral response function of the two images. The results were evaluated by comparing the Root Mean Square Error (RMSE), the Spectral Angle Mapper (SAM), and average percentage differences. The results of this study showed that the proposed method corrected the spectral information in the multispectral data by using hyperspectral data, and its performance was similar to the manual cross-calibration. The proposed method demonstrated the possibility of automatic cross-calibration based on spectral mixture analysis.

• 한국멀티미디어학회논문지
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• 제22권10호
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• pp.1142-1148
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• 2019

Reconstruction of the three-dimensional (3D) environment is a key aspect of augmented reality and augmented virtuality, which utilize and incorporate a user's surroundings. Such reconstruction can be easily realized by employing a Kinect device. However, multiple Kinect devices are required for enhancing the reconstruction density and for spatial expansion. While employing multiple Kinect devices, they must be calibrated with respect to each other in advance, and a marker is often used for this purpose. However, a marker needs to be placed at each calibration, and the result of marker detection significantly affects the calibration accuracy. Therefore, a user-friendly, efficient, accurate, and marker-less method for calibrating multiple Kinect devices is proposed in this study. The proposed method includes a joint tracking algorithm for approximate calibration, and the obtained result is further refined by applying the iterative closest point algorithm. Experimental results indicate that the proposed method is a convenient alternative to conventional marker-based methods for calibrating multiple Kinect devices. Hence, the proposed method can be incorporated in various applications of augmented reality and augmented virtuality that require 3D environment reconstruction by employing multiple Kinect devices.

• 전자공학회논문지B
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• 제29B권2호
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• pp.27-39
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• 1992

3 Dimensional measurement system using camera and laser slit-ray is studied. Precise calibration technique in this system is suggested. Calibration is accomplished with calibration die, calibration block and robot. For obtaining calibration parameters, the equations are solved using least square error method from a great many calibration points to reduce measuring error. Continuous measurement is possible for the object which is larger than one frame of camera. The efficiency and usability are proved by applying to the tire profile measuring system which measures tire profile using robot and this system.