• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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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.

• Journal of Information Display
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• v.11 no.2
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• pp.68-75
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• 2010

The relation between light sources and screen cells is considered part of the theoretical model of an autostereoscopic 3D display. The geometry of the image and observer regions is presented, including the cases of single and multiple regions. The characteristic function is introduced. Formulas for the geometric parameters are obtained, including areas and angles. Special attention is drawn to the screen location. The method of transforming the formulas between regions is stated. For multiple regions, geometric dissimilarity was found. This allows the model to be applied in finding the geometric characteristics of multiview and integral-imaging 3D displays.

• Korean Journal of Computational Design and Engineering
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• v.4 no.1
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• pp.1-11
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• 1999

surface texture denotes set of tiny repetitive geometric features on an object surface. 3D Printing can readily create a surface of controlled macro-textures of high geometric complexity. Designing surface textures for 3D Printing, however, is difficult due to complex macro-structure of the tiny texture geometry since it needs to be compatible with the non-traditioal manufacturing method. In this paper we propose a visual simulation technique involving development of a virtual model-an intermediate geometric model-of the surface texture design prior to fabricating the physical model. Careful examination of the virtual model before the actual fabrication can help minimize unwanted design iterations. The proposed technique demonstrated visualization capability by comparing the virtual model with the physical model for several test cases.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.505-518
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• 2023

3D point cloud semantic segmentation is a computer vision task that involves dividing the point cloud into different objects and regions by predicting the class label of each point. Existing 3D semantic segmentation models have some limitations in performing sufficient fusion of multi-modal features while ensuring both characteristics of 2D visual features extracted from RGB images and 3D geometric features extracted from point cloud. Therefore, in this paper, we propose MMCA-Net, a novel 3D semantic segmentation model using 2D-3D multi-modal features. The proposed model effectively fuses two heterogeneous 2D visual features and 3D geometric features by using an intermediate fusion strategy and a multi-modal cross attention-based fusion operation. Also, the proposed model extracts context-rich 3D geometric features from input point cloud consisting of irregularly distributed points by adopting PTv2 as 3D geometric encoder. In this paper, we conducted both quantitative and qualitative experiments with the benchmark dataset, ScanNetv2 in order to analyze the performance of the proposed model. In terms of the metric mIoU, the proposed model showed a 9.2% performance improvement over the PTv2 model using only 3D geometric features, and a 12.12% performance improvement over the MVPNet model using 2D-3D multi-modal features. As a result, we proved the effectiveness and usefulness of the proposed model.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.11
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• pp.1080-1087
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• 2009

This paper presents an algorithm to acquire 3D geometric information using a virtual plane method. The method to measure 3D information on the plane is easy, because it's not concerning value on the z-axis. A plane can be made by arbitrary three points in the 3D space, so the algorithm is able to make a number of virtual planes from feature points on the target object. In this case, these geometric relations between the origin of each virtual plane and the origin of the target object coordinates should be expressed as known homogeneous matrices. To include this idea, the algorithm could induce simple matrix formula which is only concerning unknown geometric relation between the origin of target object and the origin of camera coordinates. Therefore, it's more fast and simple than other methods. For achieving the proposed method, a regular pin-hole camera model and a perspective projection matrix which is defined by a geometric relation between each coordinate system is used. In the final part of this paper, we demonstrate the techniques for a variety of applications, including measurements in industrial parts and known patches images.

• Current Optics and Photonics
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• v.6 no.2
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• pp.161-170
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• 2022

Three-dimensional (3D) geometric models are introduced to correct vignetting, and a downhill simplex search is applied to determine the coefficients of a 3D model used in digital microscopy. Vignetting is nonuniform illuminance with a geometric regularity on a two-dimensional (2D) image plane, which allows the illuminance distribution to be estimated using 3D models. The 3D models are defined using generalized polynomials and arbitrary coefficients. Because the 3D models are nonlinear, their coefficients are determined using a simplex search. The cost function of the simplex search is defined to minimize the error between the 3D model and the reference image of a standard white board. The conventional and proposed methods for correcting the vignetting are used in experiments on four inspection systems based on machine vision and microscopy. The methods are investigated using various performance indices, including the coefficient of determination, the mean absolute error, and the uniformity after correction. The proposed method is intuitive and shows performance similar to the conventional approach, using a smaller number of coefficients.

• Journal of the Korea Computer Graphics Society
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• v.9 no.2
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• pp.11-18
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• 2003

For extracting geometric features in 3D meshes according to user-steering with effective interactions. this paper generalizes the 2D algorithms of snapping and wrapping that. respectively. moves a cursor to a nearby feature and constructs feature boundaries. First. we define approximate curvatures and move cost functions that are the numerical values measuring the geometric characteristics of the meshes, By exploiting the measuring values. the algorithms of geometric snapping and geometric wrapping are developed and implemented. We also visualize the results from applying the algorithms to extracting geometric features of general 3D mesh models such as a face model and a tooth model.

• Korean Journal of Computational Design and Engineering
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• v.15 no.3
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• pp.234-242
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• 2010

3D CAD technology has been extended to a medical area including dental clinic beyond industrial design. The 2D images obtained by CT(Computerized Tomography) and MRI(Magnetic Resonance Imaging) are not intuitive, and thus the volume rendering technique, which transforms 2D data into 3D anatomic information, has been in practical use. This paper has focused on a method and its implementation for forming 3D geometric surface model from laminated CT images of the pubis. The implemented system could support a dental clinic to observe and examine the status of a patient's pubis before implant surgery. The supplement of 3D implant model would help dental surgeons settle operation plans more safely and confidently. It also would be utilized with teaching materials for a practice and training.

• Structural Engineering and Mechanics
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• v.48 no.5
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• pp.587-613
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• 2013

A 3-node 3D co-rotational beam element using vectorial rotational variables is employed to consider the geometric nonlinearity in 3D space. To account for shape versatility and reinforced concrete cross-sections, fibre model has been derived and conducted. Numerical integration over the cross-section is performed, considering both normal and shear stresses. In addition, the derivations associated with material nonlinearity are given in terms of elasto-plastic incremental stress-strain relationship for both steel and concrete. Steel reinforcement is treated as elasto-plastic material with Von Mises yield criterion. Compressive concrete behaviour is described by Modified Kent and Park model, while tensile stiffening effect is taken into account as well. Through several numerical examples, it is shown that the proposed 3D co-rotational beam element with fibre model can be used to simulate steel and reinforced concrete framed structures with satisfactory accuracy and efficiency.

• International journal of advanced smart convergence
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• v.5 no.4
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• pp.1-9
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• 2016

In order to reconstruct a 3D model in video sequences, to select key frames that are easy to estimate a geometric model is essential. This paper proposes a method to easily extract informative frames from a handheld video. The method combines selection criteria based on appropriate-baseline determination between frames, frame jumping for fast searching in the video, geometric robust information criterion (GRIC) scores for the frame-to-frame homography and fundamental matrix, and blurry-frame removal. Through experiments with videos taken in indoor space, the proposed method shows creating a more robust 3D point cloud than existing methods, even in the presence of motion blur and degenerate motions.