• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.100.5-100
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• 2002

A core technology for implementation of Augmented Reality is to develop a merging algorithm between interesting 3-D objects and real images. In this paper, we present a 3-D object recognition method to decide viewing direction toward the object from camera. This process is the starting point to merge with real image and 3-D objects. Perspective projection between a camera and 3-dimentional objects defines a plane in 3-D space that is from a line in an image and the focal point of the camera. If no errors with perfect 3-D models were introduced in during image feature extraction, then model lines in 3-D space projecting onto this line in the image would exactly lie in this plane. This observa...

• Journal of information and communication convergence engineering
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• 제19권2호
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• pp.102-107
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• 2021

In this paper, we propose a new three-dimensional (3D) photon-counting integral imaging reconstruction method using a merging reconstruction process and maximum likelihood estimation (MLE). The conventional 3D photon-counting reconstruction method extracts photons from elemental images using a Poisson random process and estimates the scene using statistical methods such as MLE. However, it can reduce the photon levels because of an average overlapping calculation. Thus, it may not visualize 3D objects in severely low light environments. In addition, it may not generate high-quality reconstructed 3D images when the number of elemental images is insufficient. To solve these problems, we propose a new 3D photon-counting merging reconstruction method using MLE. It can visualize 3D objects without photon-level loss through a proposed overlapping calculation during the reconstruction process. We confirmed the image quality of our proposed method by performing optical experiments.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.827-828
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• 2006

This paper presents a vehicle control algorithm for Personal Rapid Transit (PRT) system. PRT system is a one-way direction network system which is composed of guideway branches, merging/diverging points. Vehicle control algorithm can be divided into two kinds. Those are merging control algorithm and the other. We emphasized on the merging control algorithm. For that, we first devised a front/virtual front vehicle finding strategies. Properly determined front/virtual front vehicle is the starting point of vehicle control. The objects of merging control are to avoid collision and to pass the merging point fluently. Which implies that jerk constraint and limits of acceleration and deceleration etc. are should be considered. To verify the validation of the vehicle algorithm, we executed simulations and presented test results.

• 한국콘텐츠학회논문지
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• 제7권2호
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• pp.40-50
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• 2007

본 논문에서는 카메라로부터 획득 되어진 비디오 시퀀스로부터 다중 움직임 객체와 배경을 분할하고 시공간 정보에 기반 한 객체 추적 방법을 제안한다. 제안한 방법은 3단계로 구성되어 있다. 먼저 입력 비디오 시퀀스로부터 프레임 사이의 차를 이용한 움직임 영역과 움직임이 존재하지 않는 영역을 구분하여 적응적 경계간을 추출한다. 두 번째는 참조 배경영상과 적응적 경계값을 이용하여 움직임이 존재하는 영역으로부터 개략적 객체 분할을 수행하며, 분할된 이진영상에 형태학적 영역 병합 알고리즘을 적용하여 객체 병합을 수행하였다. 마지막으로 분할된 객체에 시공간 정보를 이용하여 객체에 임의의 ID를 할당하여 추적하였다. 카메라로부터 획득되어진 비디오 시퀀스를 이용한 실험에서 객체들의 분할 및 추적의 효율성과 시스템의 유용성을 확인하였다.

• 한국통신학회논문지
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• 제21권10호
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• pp.2552-2562
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• 1996

In this paper, we propose a segmentation algorithm that can reliably separate moving objects from noisy background in the image sequance received from a camera at the fixed position. The proposed algorithm consists of three processes:generation of the difference image between the input image and the reference image, multilevel quantization of the difference image, and multistagemerging in the quantized image. The quantization process requantizes the difference image based on the multiple threshold values determined bythe histogram analysis. The merging starts from the seed region which created by using the highest threshold value and ends when termination conditions are met. the proposed method has been tested with various real imge sequances containing intruders. The test results show that the proposed algorithm can detect moving objects like intruders very effectively in the noisy environment.

• 천문학회보
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• 제35권2호
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• pp.44-44
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• 2010

We study the effect of massive neutrinos on the evolution of the early mini-halos ($M\sim10^6h^{-1}M{\odot}at$ z~20) where the first stars may have formed. In the framework of the extended Press-Schechter formalism, we evaluate analytically the rates of merging of the mini-halos into zero-dimensional larger halos and one-dimensional mini-filaments. It is shown that the halo-to-filament merging rate increases with the neutrino mass fraction $f_v$ while the halo-to-halo merging rate decreases. Comparing the cases of $f_v$=0 and 0.10, the halo-to-filament merging rate for $f_v$=0.10 is 3 times larger than the other. The distribution of the epochs of the longest-axis collapse of these first filaments is also derived and found to reach a sharp maximum at z~8-9. Once the first mini-filaments form, they would provide bridges along which the matter and gas more rapidly accrete onto the constituent halos, causing the early formation of the first galaxies and rapid growth of their central blackholes. Furthermore, the longest axis collapse of these first mini-filaments would spur the supermassive blackholes to power the ultra-luminous high-z quasars.

• 천문학회지
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• 제38권3호
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• pp.345-355
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• 2005

We present a photometric study of the star cluster system in the merging galaxy NGC 1487, based on the BI photometry obtained from the F450W and F814W images in the HST /WFPC2 archive data. We have found about 560 star cluster candidates in NGC 1487, using the morphological parameters of the objects. We have investigated several photometric characteristics of the clusters: color-magnitude diagrams (CMDs), color distribution, spatial distribution, age, size and luminosity function. The CMD of the bright clusters with 18.5 < B < 24 mag in NGC 1487 shows three major populations of clusters: a blue cluster population with $(B-I){\le}0.45$, an intermediate-color cluster population with $0.45<(B-I){\le}1.55$, and a red cluster population with (B - I) > 1.55. The intermediate-color population is the most dominant among the three populations. The brightest clusters in the blue and intermediate- color populations are as bright as $B{\approx}18mag$ ($M_B{\approx}-12mag$), which are three magnitudes brighter than those in the red population. The blue and intermediate-color clusters are strongly concentrated on the bright condensations, while the red clusters are relatively more scattered over the galaxy. The CMD of these clusters is found to be remarkably similar to that of the clusters in the famous interacting system M51. From this we suggest that the intermediate-color clusters were, probably, formed during the merging process which occurred about 500 Myrs ago.

• 한국멀티미디어학회논문지
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• 제13권5호
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• pp.651-662
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• 2010

본 연구는 외부환경에서 자율주행 로봇을 위해 중요한 물체를 찾기 위한 방법을 설명한다. 외부환경의 물체를 찾기 위해서 먼저 로봇은 외부환경에서 주행할 때 획득한 영상으로부터 물체를 검출하고 분할한다. 로봇은 물체의 후보를 자연물의 하늘과 나무로, 인공물의 빌딩으로 나눈다. 후보 물체를 분할하기 위해서 다중 특징을 이용한다. 다중 특징은 색상, 선분, 상황정보, 동시발생 행렬, 소실점 및 주요한 요소성분을 이용한다. 후보 특징은 물체의 특성에 맞게 혼합하여 물체를 분할한다. 이런 다중 특징은 물체에 대한 공간정보, 인간의 선험적인 지식을 이용한 물체의 기하학 정보, 공간적인 주파수 등으로 다양한 특징 추출 방법을 이용하여 물체의 영역분할의 결과를 얻는다. 물체의 분석은 분할된 영역을 이용하여 벽 영역, 창문, 정문과 같은 빌딩면의 기하학적인 속성을 찾는다. 빌딩은 소실점의 수직선분과 수평선분을 교차함으로써 그물을 얻는다. 빌딩의 벽 영역은 유사한 색상을 가지는 이웃해 있는 평행사변형의 그물을 합병해서 검출한다. 창문은 층의 수와 동일한 층에 있는 방의 수를 추정하여 빌딩의 높이와 크기를 추정한다. 실험에서 다중 특징을 이용하여 물체의 영역을 분할하고 빌딩의 기하학적인 속성을 이용하여 물체를 분석한다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.363-363
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• 2000

The conventional algorithms which identify and follow a moving target using a camera located at a fixed position are not appropriate for applying to the cases o( using mobile robots, due to their long processing time. This paper proposes a new tracking algorithm based on the sensing system which uses a line light with a single camera. The algorithm categirizes the motion patterns of a pair of mobile objects into parallel, branching, and merging motion, to decide of which objects the trajectories should be calculated to follow the reference object. Kalman Filter is used to estimate the trajectories of selected objects. The proposed algorithm has shown in the experiments that the mobile robot does not miss the target in most cases.

• 대한산업공학회지
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• 제29권1호
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• pp.90-99
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• 2003

Object clustering, which makes classification for a set of objects into a number of groups such that objects included in a group have similar characteristic and objects in different groups have dissimilar characteristic each other, has been exploited in diverse area such as information retrieval, data mining, group technology, etc. In this study, an object-clustering problem with similarity coefficients between objects is considered. At first, an evaluation function for the optimization problem is defined. Then, a genetic algorithm and local optimization technique based on heuristic method are proposed and used in order to obtain near optimal solutions. Solutions from the genetic algorithm are improved by local optimization techniques based on object relocation and cluster merging. Throughout extensive experiments, the validity and effectiveness of the proposed algorithms are tested.