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      스테레오 비전 시스템을 이용한 3차원 형상모델 생성 = 3D shape model generation based on a stereo vision system

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      https://www.riss.kr/link?id=A75066561

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      다국어 초록 (Multilingual Abstract)

      3D shape 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 more fast. In this paper, we address 3D geometric model generation based on a stereo vision system (SVS). 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, correspondence, scanning from multiple views, noise handling, registration, and triangular mesh generation. We propose several tips that are helpful for users' convenience and the quality of the results during the model generation process. Examples are given to show their usefulness.
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      3D shape 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 s...

      3D shape 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 more fast. In this paper, we address 3D geometric model generation based on a stereo vision system (SVS). 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, correspondence, scanning from multiple views, noise handling, registration, and triangular mesh generation. We propose several tips that are helpful for users' convenience and the quality of the results during the model generation process. Examples are given to show their usefulness.

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