• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.99.5-99
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• 2002

$\textbullet$ 3-D object tracking framework $\textbullet$ Using fast stereo vision system for range image $\textbullet$ Using CONDENSATION algorithm to tracking object $\textbullet$ For recognizing object, superquardrics model is used $\textbullet$ Our target object is like coils in steel works

• 대한임베디드공학회논문지
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• 제3권3호
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• pp.143-150
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• 2008

In this paper, we investigate a real-time environment recognition system based on stereo vision for moving object. This system consists of stereo matching, obstacle detection and distance estimation. In stereo matching part, depth maps can be obtained real road images captured adjustable baseline stereo vision system using belief propagation(BP) algorithm. In detection part, various obstacles are detected using only depth map in case of both v-disparity and column detection method under the real road environment. Finally in estimation part, asymmetric parabola fitting with NCC method improves estimation of obstacle detection. This stereo vision system can be applied to many applications such as unmanned vehicle and robot.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2004년도 추계학술대회 논문집
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• pp.454-457
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• 2004

AGV for FMS must be detected an obstacle. Therefore, many studies have been advanced, and recently, the ultra sonic sensor is used for this. However, the new method has to be developed because the ultra-sonic-sensor has many problems as a noise in factory, an directional error and detection of the obstacle size. So, we study the fast stereo vision system that can give more information to obstacles for intelligent AGV system. For this, the simulated AGV system was made with two CCD cameras in front to get the stereo images, and the threshold process by color information (intensity and chromaticity) and structure stereo matching method were constructed.

• Journal of information and communication convergence engineering
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• 제12권2호
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• pp.128-134
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• 2014

In this paper, we present a graphics processing unit (GPU)-based matching technique for the purpose of fast feature matching between different images. The scale invariant feature transform algorithm developed by Lowe for various feature matching applications, such as stereo vision and object recognition, is computationally intensive. To address this problem, we propose a matching technique optimized for GPUs to perform computations in less time. We optimize GPUs for fast computation of keypoints to make our system quick and efficient. The proposed method uses a self-organizing map feature matching technique to perform efficient matching between the different images. The experiments are performed on various image sets to examine the performance of the system under varying conditions, such as image rotation, scaling, and blurring. The experimental results show that the proposed algorithm outperforms the existing feature matching methods, resulting in fast feature matching due to the optimization of the GPU.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2007년도 하계종합학술대회 논문집
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• pp.205-206
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• 2007

In stereo vision applications, disparity estimation is often performed to corresponding pixels. Using window-based correlations is a fast and standard approach to the disparity estimation. In this paper, we analyse the behaviour of the correlation-based disparity estimation and improve its performance by combining it with a segmentation scheme. Simulation results demonstrate that the proposed algorithm provides faithful disparity maps.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
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• pp.848-853
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• 2005

3D geometric modeling of an object of interest has been intensively investigated in many fields including CAD/CAM and computer graphics. Traditionally, CAD and geometric modeling tools are widely used to create geometric models that have nearly the same shape of 3D real objects or satisfy designers intent. Recently, with the help of the reverse engineering (RE) technology, we can easily acquire 3D point data from the objects and create 3D geometric models that perfectly fit the scanned data more easily and fast. In this paper, we present 3D geometric model generation based on a stereo vision system (SVS) using random pattern projection. A triangular mesh is considered as the resulting geometric model. In order to obtain reasonable results with the SVS-based geometric model generation, we deal with many steps including camera calibration, stereo matching, scanning from multiple views, noise handling, registration, and triangular mesh generation. To acquire reliable stere matching, we project random patterns onto the object. With experiments using various random patterns, we propose several tips helpful for the quality of the results. Some examples are given to show their usefulness.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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• pp.202-204
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• 2006

In this paper, the detection scheme of the spatial coordinates based on stereo camera for a Transformation algorithm of an Leg-wheel Hexapod Robot is proposed. Robot designed as can have advantages that do transfer possibility fast mobility in flat topography and uneven topography through walk that use wheel drive. In the proposed system, using the disparity data obtained from the left and right images captured by the stereo camera system and the perspective transformation between a 3-D scene and an image plane, depth information can be detected. Robot uses construed environmental data and transformation algorithm, decide wheel drive and leg waik, and can calculate width of street and regulate width of robot.

• 한국정보통신학회논문지
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• 제20권10호
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• pp.2001-2006
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• 2016

감마선 공간 탐지 장치는 감마선원을 스캔하여 영상화 한 후 스테레오 영상처리기술을 적용하여 탐지선원까지의 거리를 측정한다. 또한 실제 공간의 방사선원에 대한 분포 정보를 제공해 준다. 본 논문에서는 감마선 탐지장치가 3차원 공간상에서 장치로부터 선원을 찾기 위해 스캔하는 탐지 시간을 단축 시킬 수 있도록 감마선 탐지 고속화 알고리즘을 구현하였다. 그리고 감마선 조사 시험장에서 실험을 통해 그 성능을 검증하였다. 탐지시험 결과 고속 탐지를 위한 알고리즘을 적용할 경우 단일선원을 탐지할 경우 좌 우 스테레오 영상 획득 시보다 약 35% 의 탐지 시간을 단축시킬 수 있음을 확인하였다. 또한 사용자에게 방사선 공간분포 정보를 효율적으로 전달하기 위한 감마선원 분포의 입체 가시화를 구현하여 방사선원에 대한 정보를 제공할 수 있도록 하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.729-734
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• 2005

One of the important research issues in mobile robot is how to detect the 3D environment fast and accurately, and recognize it. Sensing methods of utilizing laser structured light and/or stereo vision are representatively used among a number of methodologies developed to date. However, the methods are still in need of achieving high accuracy and reliability to be used for real world environments. In this paper to implement a new robotic environmental sensing algorithm is presented by combining the information between intensity image and that of laser structured light image. To see how effectively the algorithm applied to real environments, we developed a sensor system that can be mounted on a mobile robot and tested performance for a series of environments.

• 디지털콘텐츠학회 논문지
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• 제17권6호
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• pp.523-529
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• 2016

스테레오 매칭 알고리즘은 컴퓨터 비전과 사진촬영에 필수적인 알고리즘으로 정확도와 복잡도는 스테레오 매칭 알고리즘의 주요 문제점이었다. 그 중에서도 복잡도가 높은 문제점을 극복하기 위해 비용 볼륨 필터링을 기반한 스테레오 매칭 알고리즘에 대한 많은 연구가 이루어졌다. 지역 스테레오 매칭 기술인 유도 영상 필터링 기술은 O(N)의 복잡도를 가지고 있지만, 여전히 실시간 3D 비디오 서비스를 제공하기에는 계산량이 많은 편이다. 따라서 본 논문에서 고속 유도 영상 필터링에 기반한 스테레오 매칭 알고리즘을 제안한다. 고속 유도 필터링은 서브샘플 비율 $\small{s}$에 따라 복잡도 $O(N/\small{s}^2)$을 가지는 알고리즘이다. 제안하는 알고리즘은 효과적인 스테레오 알고리즘을 성능을 보여줌과 동시에 3D 서비스를 위한 빠른 실행 시간을 보여준다.