• Proceedings of the Computational Structural Engineering Institute Conference
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• 2010.04a
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• pp.238-241
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• 2010

This paper proposed an approach to integrate bridge condition assessment related information with a 3D bridge model to visualize bridge condition assessment information in the 3D bridge model. In this approach, bridge information model plays a centric role in the data access and realizes the integration of bridge initial design and historical bridge maintenance records. Behind the bridge information model is a rational database. After the system requirements for this approach, several IFC data model extensions are suggested.

• Korean Journal of Computational Design and Engineering
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• v.14 no.6
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• pp.415-423
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• 2009

Because of the fast changing car design and increasing facilities, manufacturing process of cars is getting more complex now a days. Particularly, car manufacturing system that consist of automated devices, applies various simulation techniques to validate device motion and detect collision. To cope with this problem, traditional manufacturing system deployed test-run with the real devices. However, increased computing power in a contemporary manufacturing system changes it into realistic 3D simulation environment. Similarly, managed device data that was generated using 2D traditionally, can be converted to 3D realistic simulation. The existing problem with 3D simulation is disjoint data interaction between different work stations. Consequently, JIGs, fixing the car part accurately, are changed according to fixing position on the part or a part shape properties. In practice, the 3D JIG data has to be managed according to kinematic information, but not of its features. However, generating kinematic information to the 3D model repeatedly according to frequent change in part is not explained in current literatures. To fill this knowledge gap, this paper suggests an improving method of rendering 3D JIG kinematics information to simulation model. Thereafter, it shows the result of implementation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.410-413
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• 2001

This paper is to model a 3D-shape product applying mathematically the data acquired from a 3D scanner and using an Automatic Design Program. The research studied in the reverse engineering up to now has been developed continuously and surprisingly. However, forming 3D-shape solid models in CAE and CAM, based on the research, the study leaves much to be desired. Especially, analyses and studies reverse-designing automatically using measured data after manufacturing. Consequently, we are going to acquire geometric data using an 3D scanner in this study with which we will open a new field of reverse engineering by a program whic hcan design a 3D-shape solid model in a CAD-based program automatically.

• Journal of Korea Multimedia Society
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• v.22 no.12
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• pp.1385-1395
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• 2019

In this paper, we propose a method to fabricate a patient-specific breast implant using MRI images and 3D scan data. Existing breast implants for breast reconstruction surgery are primarily fabricated products for shaping, and among the limited types of implants, products similar to the patient's breast have been used. In fact, the larger the difference between the shape of the breast and the implant, the more frequent the postoperative side effects and the lower the satisfaction. Previous researches on the fabrication of patient-specific breast implants have used limited information based on only MRI images or on only 3D scan data. In this paper, we propose an algorithm for the fabrication of patient-specific breast implants that combines MRI images with 3D scan data, considering anatomical suitability for external shape, volume, and pectoral muscle. Experimental results show that we can produce precise breast implants using the proposed algorithm.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.859-861
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• 2003

In order to present a space in details, it is indispensable to acquire 3D shape and texture simultaneously from the same platform. 3D shape is acquired by Laser Scanner as point cloud data, and texture is acquired by CCD sensor. Positioning data is acquired by IMU (Inertial Measurement Unit). All the sensors and equipments are assembled on a hand-trolley. In this research, a method of integrating the 3D shape and texture for automated construction of Digital Surface Model is developed. This Digital Surface Model is applied for efficient feature extraction. More detailed extraction is possible , because 3D Digital Surface Model has both 3D shape and texture information.

• Journal of the Korea Computer Graphics Society
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• v.24 no.4
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• pp.11-20
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• 2018

Applications about systems integration of sensors and virtual environments have been developed increasingly. Accordingly, there is a need for the ability to represent, control, and manage physical sensors directly in a 3D virtual environment. In this research, a method of representing physical sensor devices in a 3D virtual environment has been defined using mixed and augmented reality, including virtual and real worlds, where sensors and virtual objects co-exist. The research is intended to control and manage various physical sensors through data sharing and interchange between heterogeneous computing environments. In order to achieve this, general sensor types have been classified, and a sensor based 3D scene graph for representing the functions of sensors has been defined. In addition, a sensor data model has been defined using the scene graph. Finally, a sensor 3D viewer has been implemented based on the scene graph and the data model so as to simulate the functions of sensors in indoor and outdoor 3D environments.

• Journal of the Society of Disaster Information
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• v.19 no.4
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• pp.897-907
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• 2023

Purpose: In this study, We aim to estimate a untrained person's three postures using a 2D CNN model which is trained with minimal FFT data collected by a 24GHz FMCW radar. Method: In an indoor space, we collected FFT data for three distinct postures (standing, sitting, and lying) from three different individuals. To apply this data to a 2D CNN model, we first converted the collected data into 2D images. These images were then trained using the 2D CNN model to recognize the distinct features of each posture. Following the training, we evaluated the model's accuracy in differentiating the posture features across various individuals. Result: According to the experimental results, the average accuracy of the proposed scheme for the three postures was shown to be a 89.99% and it outperforms the conventional 1D CNN and the SVM schemes. Conclusion: In this study, we aim to estimate any person's three postures using a 2D CNN model and a 24GHz FMCW radar for disastrous situations in indoor. it is shown that the different posture of any persons can be accurately estimated even though his or her data is not used for training the AI model.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.1
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• pp.73-83
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• 2008

For spatial analysis and decision-making based on territorial and urban information, technologies on 3D GIS with digital image data and photo-realistic 3D image models to visualize 3D modeling are being rapidly developed. Currently, satellite images, aerial images and aerial LiDAR data are mostly used to build 3D models and textures from oblique aerial photographs or terrestrial photographs are used to create 3D image models. However, we are in need of quality 3D image models as current models cannot express topographic and features most elaborately and realistically. Thus, this study analyzed techniques to use aerial photographs, aerial LiDAR, terrestrial photographs and terrestrial LiDAR to create a 3D image model with artificial features and special topographic that emphasize spatial accuracy, delicate depiction and photo-realistic imaging. A 3D image model with spatial accuracy and photographic texture was built to be served via 3D image map services systems on the Internet. As it was necessary to consider intended use and display scale when building 3D image models, in this study, we applied the concept of LoD(Level of Detail) to define 3D image model of buildings in five levels and established the models by following the levels.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.435-438
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• 2001

Reverse engineering technology refers to the process that creates a CAD model of an existing part using measuring devices. Recently, non-contact scanning devices have become more accurate and the speed of data acquisition has increased drastically. However, they generate thousands of points per second and various types of point data. Therefore, it becomes a major issue to handle the huge amount and various types of point data. To generate a CAD model from scanned point data efficiently, these point data should be well arranged through point data handling processes such as data reduction and segmentation. This paper proposes a new point data handling method using 3D grids. The geometric information of a part is extracted from point cloud data by estimating normal values of the points. The non-uniform 3D grids for data reduction and segmentation are generated based on the geometric information. Through these data reduction and segmentation processes, it is possible to create CAD models autmatically and efficiently. The proposed method is applied to two quardric medels and the results are discussed.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.773-775
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• 2003

From the view point of data fusion, we integrate LIDAR data and digital aerial images to perform 3D building modeling in this study. The proposed scheme comprises two major parts: (1) building block extraction and (2) building model reconstruction. In the first step, height differences are analyzed to detect the above ground areas. Color analysis is then performed for the exclusion of tree areas. Potential building blocks are selected first followed by the refinement of building areas. In the second step, through edge detection and extracting the height information from LIDAR data, accurate 3D edges in object space is calculated. The accurate 3D edges are combined with the already developed SMS method for building modeling. LIDAR data acquired by Leica ALS 40 in Hsin-Chu Science-based Industrial Park of north Taiwan will be used in the test.