• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.751-752
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• 2010

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.1013-1014
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• 2010

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.939-946
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• 2018

In this paper, we implement a viewer program that can monitor effectively using omni-directional images. The program consists of four modes: Normal mode, ROI(Region of Interest) mode, Tracking mode, and Auto-rotation mode, and the results for each mode is displayed simultaneously. In the normal mode, the wide angle image is rendered as a spherical image to enable pan, tilt, and zoom. In ROI mode, the area is displayed expanded by selecting an area. And, in Auto-rotation mode, it is possible to track the object by mapping the position of the object with the rotation angle of the spherical image to prevent the object from deviating from the spherical image in Tracking mode. Parallel programming for processing of multiple modes is performed to improve the processing speed. This has the advantage that various angles can be seen compared with surveillance system having a limited angle of view.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.58.1-58.1
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• 2013

The main idea of the Alcock-Paczynski (AP) test is that, if we use a wrong distance-redshift relation to infer the shape of a spherical object in the Universe, this object may look non-spherical. To probe the cosmic expansion history through the AP test, the key point is to find something which is known as spherical in the Universe. We propose two possible ways applying the AP test to the large scale structure (LSS): 1) Based on the observed galaxies or quasars, one built up the beta-skeleton tracing the LSS, and investigating the inhomogeneity of the connections; 2) One reconstructs the smoothed density-contrast gradient field based on LSS observations, and investigating the inhomogeneity of the gradient vectors. Compared with some existed methods probing AP effect through 2-point correlation function, galaxy pairs, or voids, our methods have various advantages: 1) The information of both the high and low dense regions of the LSS are taken into account. 2) The redshift space distortion as the main contamination to the AP effect can be easily removed.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.6
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• pp.23-29
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• 2016

In this paper, we propose a method of depth video coding to find the closest sphere through the depth information when the spherical object is captured. We find the closest sphere to the captured spherical object using method of least squares in each block. Then, we estimate the depth value through the found sphere and encode the depth video through difference between the measured depth values and the estimated depth values. Also, we encode factors of the estimated sphere with encoded pixels within the block. The proposed method improves the coding efficiency up to 81% compared to the conventional DPCM method.

• Bulletin of the Korean Mathematical Society
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• v.43 no.1
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• pp.189-212
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• 2006

Let $F^{\alpha}G$ be a twisted group algebra with basis ${{\mu}g|g\;{\in}\;G}$ and $P\;=\;{C_g|g\;{\in}\;G}$ be a partition of G. A projective class algebra associated with P is a subalgebra of $F^{\alpha}G$ generated by all class sums $\sum\limits{_{x{\in}C_g}}\;{\mu}_x$. A main object of the paper is to find interrelationships of projective class algebras in $F^{\alpha}G$ and in $F^{\alpha}H$ for H < G. And the a-spherical function will play an important role for the purpose. We find functional properties of a-spherical functions and investigate roles of $\alpha-spherical$ functions as characters of projective class algebras.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.5
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• pp.9-11
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• 2001

• Journal of the Optical Society of Korea
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• v.5 no.4
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• pp.140-145
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• 2001

We present a new method of volumetric interferometer, which is intended to measure the three-dimensional coordinates of a moving object in a simultaneous way with a single optical setup. The method is based on the principles of phase-measuring interferometry with phase shifting. Two diffraction point sources, which are made of the polished ends of single-mode optical fibers are embedded on the object. Two spherical wavefronts emanate from the diffraction point sources and interfere with each other within the measurement volume. One wavefront is phase-shifted by elongating the corresponding fiber using a PZT extender. A CCD array sensor fixed at the stationary measurement station detects the resulting interference field. The measured phases are then related to the three-dimensional location of the object with a set of non-liner equations of Euclidean distance, from which the complete set of three-dimensional spatial coordinates of the object is determined through rigorous numerical computation based upon the least square error minimization.

• 한국정보디스플레이학회:학술대회논문집
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• 2002.08a
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• pp.395-398
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• 2002

The spherical aberration and optical integer (f) of the electron gun's main lens in color CRT is obtained, using electron beam trajectory. A spherical aberration is obtained from the relation between the object plane and the image of a beam trajectory. To analyze beam profile, 3rd and 1st order coefficient were obtained and used. It is shown that, in practice, they are applied to electron gun design.

• Journal of Broadcast Engineering
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• v.28 no.3
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• pp.329-332
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• 2023

3D Object Detection using deep neural network has been developed a lot for obstacle detection in autonomous vehicles because it can recognize not only the class of target object but also the distance from the object. But in the case of 3D Object Detection models, the detection performance for distant objects is lower than that for nearby objects, which is a critical issue for autonomous vehicles. In this paper, we introduce a technique that increases the performance of 3D object detection models, particularly in recognizing distant objects, by generating virtual 3D vehicle data and adding it to the dataset used for model training. We used a spherical point tracing method that leverages the characteristics of 3D LiDAR sensor data to create virtual vehicles that closely resemble real ones, and we demonstrated the validity of the virtual data by using it to improve recognition performance for objects at all distances in model training.