• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.05a
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• pp.17-18
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• 2015

In manufacturing industry, image scanning technique has made enormous progress in past decades. 3D models have been also very important to continuously monitor the related spatial information for freeform buildings. The process of shape making of 3D scanning is as follows: mesh surface segmentation, NURBS surface generation, and parametric solid model generation. We will review the process and applying process. Especially in the construction industry, 3D data collection by laser scanning has become an high quality 3D models. Therefore, in this research, we have an effort to review construction of reverse design process for freeform envelope using 3D scanning. The technology enables many 3D shape engineering and design parameterization of reverse engineering in the construction site.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.809-812
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• 2007

Automatic generation method of structural analysis model data for a truss bridge is presented through 3-D bridge information modeling based on Industry Foundation Classes(IFC). The mapping schema is proposed between a steel bridge information model based on STEP and a truss bridge information model based on the IFC. The geometry information from mapping is presented by IFC model, and SAP 2000 that can import the IFC file performs the structural analysis. Numerical analysis for a truss bridge is performed in this paper.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.304-306
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• 2004

With the developing of current multimedia broadcasting, user will be provided for lots of various content through the various channel and media. Content provider and consumer want the various service using content with the better quality which is fit to users' preference. For transmitting this content in the limited transmission channel capacity, it needs to transmit the highly compressed content. The content of 3D mesh model-based on MPEG-4 enables the various content service that provides the lower size and the resonable quality, and Personalize(Targeting) service just provide the contents that user more wants and likes. This paper presents the study on the targeting service using compression of 3D mesh model-based on MPEG-4 and the adaptation of Embedded Graphic application program using it.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.1
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• pp.34-40
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• 2005

In this paper, we describe the modeling for the 3D robot laser scanning system consisting of a laser stripe projector, camera, and 5-DOF robot and propose its calibration method. Nonlinear radial distortion in the camera model is considered for improving the calibration accuracy. The 3D range data is calculated using the optical triangulation principle which uses the geometrical relationship between the camera and the laser stripe plane. For optimal estimation of the system model parameters, real-coded genetic algorithm is applied in the calibration process. Experimental results show that the constructed system is able to measure the 3D position within about 1mm error. The proposed scheme could be applied to the kinematically dissimilar robot system without losing the generality and has a potential for recognition for the unknown environment.

• Smart Structures and Systems
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• v.20 no.6
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• pp.697-708
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• 2017

Maintenance plays a critical role in the bridge industry, but actual practices show many limitations because of traditional, 2D-based information systems. It is necessary to develop a new generation of maintenance information management systems for more reliable decision making in bridge maintenance. Enhancing current work processes requires a BIM-based 3D digital model that can use information from the whole lifecycle of a project (design, construction, operation, and maintenance) through continuous exchanges and updates from each stakeholder. This study describes the development of a data scheme for maintenance of cable-stayed bridges. We implemented the proposed system for a cable-stayed bridge and discussed its effectiveness.

• The Journal of the Korea Contents Association
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• v.12 no.9
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• pp.136-145
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• 2012

This research proposes a pattern making method for women's bodice by the characters of body types and develops bodice dress forms on their body shapes applying 3D body scan data. 515 women's body scan data was collected and analyzed factor and cluster analysis. Three body types were characterized in normal, obese, and slim group. In each group, 10 subjects were selected. 20 parts in 3D anthropometric data were measured using Autocad program. The amount of waist dart was calculated and three types of basic bodice pattern were developed using the calculated darts data. The amount and the position of front dart and side dart were different at obese group in comparison of normal and thin group. The three types of basic bodice model were made by the basic bodice pattern, and each model was scanned by 3D scanner to make 3D bodice dress forms. Three types of bodice dress forms were rendered using 3D max program. Bodice dress forms had the dart lines and were useful to draft patterns to fit their body shape.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2004.03a
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• pp.825-830
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• 2004

A numerical analysis based on two-dimensional and three-dimensional incompressible Navier-Stokes equations has been carried out for double-circular-arc (DCA) compressor cascades. Two types of double-circular-arc cascades were used in this analysis. The appropriate turbulence model for compressor analysis was selected among the conventional turbulence models such as Baldwin-Lomax, k-$\varepsilon$ and k-$\varepsilon$ models. The results of current study were compared with available experimental data at various incidence angles. The 2-D and 3-D computational codes based on SIMPLE/PWIM algorithm for collocated grid and hybrid scheme for the convective terms were the main features of numerical tools. As commonly known, turbulence modeling is very important for the prediction of cascade flows, which are extremely complex with separation and reattachment by adverse pressure gradient. For selection of turbulence model, 2-D analysis was performed. And then, k-$\varepsilon$ turbulence model with wall function chosen as the reasonable turbulence model for 3-D calculation was used to increase the efficiency of computation times. A reasonable result of 3-D flow pattern passing through the double-circular-arc cascade was obtained.

• The KIPS Transactions:PartB
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• v.16B no.1
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• pp.47-54
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• 2009

Automatic object recognition in 3D measuring data is of great interest in many application fields e.g. computer vision, reverse engineering and digital factory. In this paper we present a software tool for a fully automatic object detection and parameter estimation in unordered and noisy point clouds with a large number of data points. The software consists of three interactive modules each for model selection, point segmentation and model fitting, in which the orthogonal distance fitting (ODF) plays an important role. The ODF algorithms estimate model parameters by minimizing the square sum of the shortest distances between model feature and measurement points. The local quadric surface fitted through ODF to a randomly touched small initial patch of the point cloud provides the necessary initial information for the overall procedures of model selection, point segmentation and model fitting. The performance of the presented software tool will be demonstrated by applying to point clouds.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.6 s.312
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• pp.28-35
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• 2006

Statistical models of shape variability based on active shape models (ASMs) have been successfully utilized to perform segmentation and recognition tasks in two-dimensional (2D) images. Three-dimensional (3D) model-based approaches are more promising than 2D approaches since they can bring in more realistic shape constraints for recognizing and delineating the object boundary. For 3D model-based approaches, however, building the 3D shape model from a training set of segmented instances of an object is a major challenge and currently it remains an open problem in building the 3D shape model, one essential step is to generate a point distribution model (PDM). Corresponding landmarks must be selected in all1 training shapes for generating PDM, and manual determination of landmark correspondences is very time-consuming, tedious, and error-prone. In this paper, we propose a novel automatic method for generating 3D statistical shape models. Given a set of training 3D shapes, we generate a 3D model by 1) building the mean shape fro]n the distance transform of the training shapes, 2) utilizing a tetrahedron method for automatically selecting landmarks on the mean shape, and 3) subsequently propagating these landmarks to each training shape via a distance labeling method. In this paper, we investigate the accuracy and compactness of the 3D model for the human liver built from 50 segmented individual CT data sets. The proposed method is very general without such assumptions and can be applied to other data sets.

• Journal of the Korean Geotechnical Society
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• v.37 no.5
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• pp.47-63
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• 2021

Recently, the demand for three-dimensional (3D) underground maps from the perspective of digital twins and the demand for linkage utilization are increasing. However, the vastness of national geotechnical survey data and the uncertainty in applying geostatistical techniques pose challenges in modeling underground regional geotechnical characteristics. In this study, an optimal learning model based on multi-layer perceptron (MLP) was constructed for 3D subsurface lithological and geotechnical classification in Seoul, South Korea. First, the geotechnical layer and 3D spatial coordinates of each borehole dataset in the Seoul area were constructed as a geotechnical database according to a standardized format, and data pre-processing such as correction and normalization of missing values for machine learning was performed. An optimal fitting model was designed through hyperparameter optimization of the MLP model and model performance evaluation, such as precision and accuracy tests. Then, a 3D grid network locally assigning geotechnical layer classification was constructed by applying an MLP-based bet-fitting model for each unit lattice. The constructed 3D geotechnical layer map was evaluated by comparing the results of a geostatistical interpolation technique and the topsoil properties of the geological map.