• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.1003-1004
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• 2008

In this paper, we propose a 3D modeling method using Laser Slit Beam and Stereo Camera. We can get depth information of image by analyzing projected Laser Slit Beam on object. 3D modeling is demanded exquisite merge of 3D data. In our approach, we can get the depth image where the reliability is high. Each reconstructed 3D modeling is combined by the sink information which is acquired by SIFT (Scale Invariant Feature Transform) Algorithm. We perform experiments using indoor images. The results show that the proposed method works well in indoor environments

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.57-59
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• 2003

Digital surface model generation from IKONOS stereo imagery is a new challenge in photogrammetric community, especially when the satellite company does not provide the raw data as well as their ancillary ephemeris data. In this paper we utilized an estimated relief displacement azimuth and the nominal collection elevation data included in the metadata file to correct the relief displacement of GCPs, together with a linear transformation for geometric modeling of IKONOS imagery. Space intersection is performed by the trigonometric intersection assuming a parallel projection of IKONOS imagery due to its small FOV and frame size. In the experiment, less than 2-meters of RMSE in orbit modeling is achieved denoting the potential positioning accuracy of the IKONOS stereo imagery.

• 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.

• 한국군사과학기술학회지
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• 제11권4호
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• pp.107-115
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• 2008

Accurate extraction of traversable region is a critical issue for autonomous navigation of unmanned ground vehicle(UGV). This paper introduces enhanced extraction of traversable region by combining scene clustering with 3D world modeling using CCD(Charge-Coupled Device)/IR(Infra Red) image. Scene clustering is developed with K-means algorithm based on CCD and IR image. 3D world modeling is developed by fusing CCD and IR stereo image. Enhanced extraction of traversable regions is obtained by combining feature of extraction with a clustering method and a geometric characteristic of terrain derived by 3D world modeling.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2001년도 춘계학술대회 논문집
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• pp.590-593
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• 2001

In this paper we describe the 6-axes robot's position determination using a stereo vision and an image based control method. When use a stereo vision, it need a additional time to compare with mono vision system. So to reduce the time required, we use the stereo vision not image Jacobian matrix estimation but depth estimation. Image based control is not needed the high-precision of camera calibration by using a image Jacobian. The experiment is executed as devide by two part. The first is depth estimation by stereo vision and the second is robot manipulator's positioning.

• 전자공학회논문지B
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• 제30B권6호
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• pp.59-66
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• 1993

Stereo vision is useful in obtaining three dimensional depth information from two images taken from different view points. Neural network modeling for stereo matching, the key step in stereo vision, is defined by an energy function satisfying with three constraints proposed by Marr and Poggio. Stereo matching is then carried out through the network to find minimum energy corresponding to the optimized solution of the problem. An algorithm for stereo matching using an analog neural network is presented here. The network can reduce errors in initial state an early iteration steps by adoption of continuous sigmoid function in stead of binary state. The experimental results show good matching performance for sparse random dot stereogram and real image.

• 대한기계학회논문집A
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• 제27권7호
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• pp.1110-1119
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• 2003

This paper deals with the synthesis of the 3-dimensional grasp planning for unknown objects. Previous studies have many problems, which the estimation time for finding the grasping points is much long and the analysis used the not-perfect 3-dimensional modeling. To overcome these limitations in this paper new algorithm is proposed, which algorithm is achieved by two steps. First step is to find the whole 3-dimensional geometrical modeling for unknown objects by using stereo matching. Second step is to find the optimal grasping points for unknown objects by using the neural network trained by the result of optimization using genetic algorithm. The algorithm is verified by computer simulation, comparing the result between neural network and optimization.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.34.5-34
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• 2002

In this paper we propose a new method for modeling indoor environment with stereo camera and suggest a localization method for mobile robot navigation on the basis of it. From the viewpoint of easiness in map building and exclusion of artificiality, the main idea of this paper is that environment is represented as global topological map and each node has omni-directional metric and color information by using stereo camera and pan/tilt mechanism. We use the depth and color information itself in image pixel as feature for environmental abstraction. In addition, we use only the depth and color information at horizontal centerline in image, where optical axis is passing. The usefulness of this m...

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.181.5-181
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• 2001

This paper presents the method of 3D reconstruction of the depth information from the endoscopic stereo scopic images. After camera modeling to find camera parameters, we performed feature-point based stereo matching to find depth information. Acquired some depth information is finally 3D reconstructed using the NURBS(Non Uniform Rational B-Spline) algorithm. The final result image is helpful for the understanding of depth information visually.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.541-541
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• 2000

This paper Presents the method of 3D reconstruction of the depth information from the endoscopic stereo scopic images. After camera modeling to find camera parameters, we peformed feature-point based stereo matching to find depth information. Acquired some depth information is finally 3D reconstructed using the NURBS(Non Uniform Rational B-Spline) algorithm. The final result image is helpful for the understanding of depth information visually.