• International conference on construction engineering and project management
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• 2015.10a
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• pp.674-675
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• 2015

A 3D indoor model becomes an indiscernible component of BIM (Building Information Modeling) and GIS (Geographic Information System). However, a huge amount of time and human resources are inevitable for collecting spatial measurements and creating such a 3D indoor model. Also, a varied forms of 3D indoor models exist depending on their purpose of use. Thus, in this study, three different 3D indoor models are defined as 1) omnidirectional images, 2) a 3D realistic model, and 3) 3D indoor as-built model. A series of reconstruction methods is then introduced to construct each type of 3D indoor models: they are an omnidirectional image acquisition method, a hybrid surveying method, and a terrestrial LiDAR-based method. The reconstruction methods are applied to a large and complex atrium, and their 3D modeling results are compared and analyzed.

• The Korean Journal of Nuclear Medicine Technology
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• v.15 no.1
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• pp.17-24
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• 2011

Purpose: Presently in the nuclear medicine field, the high-speed image reconstruction algorithm like the OSEM algorithm is widely used as the alternative of the filtered back projection method due to the rapid development and application of the digital computer. There is no to relate and if it applies the optimal parameter be clearly determined. In this research, the quality change of the Jaszczak phantom experiment and brain SPECT patient data according to the iteration times and subset number change try to be been put through and analyzed in 3D OSEM reconstruction method of applying 3D beam modeling. Materials and Methods: Patient data from August, 2010 studied and analyzed against 5 patients implementing the brain SPECT until september, 2010 in the nuclear medicine department of ASAN medical center. The phantom image used the mixed Jaszczak phantom equally and obtained the water and 99mTc (500 MBq) in the dual head gamma camera Symbia T2 of Siemens. When reconstructing each image altogether with patient data and phantom data, we changed iteration number as 1, 4, 8, 12, 24 and 30 times and subset number as 2, 4, 8, 16 and 32 times. We reconstructed in reconstructed each image, the variation coefficient for guessing about noise of images and image contrast, FWHM were produced and compared. Results: In patients and phantom experiment data, a contrast and spatial resolution of an image showed the tendency to increase linearly altogether according to the increment of the iteration times and subset number but the variation coefficient did not show the tendency to be improved according to the increase of two parameters. In the comparison according to the scan time, the image contrast and FWHM showed altogether the result of being linearly improved according to the iteration times and subset number increase in projection per 10, 20 and 30 second image but the variation coefficient did not show the tendency to be improved. Conclusion: The linear relationship of the image contrast improved in 3D OSEM reconstruction method image of applying 3D beam modeling through this experiment like the existing 1D and 2D OSEM reconfiguration method according to the iteration times and subset number increase could be confirmed. However, this is simple phantom experiment and the result of obtaining by the some patients limited range and the various variables can be existed. So for generalizing this based on this results of this experiment, there is the excessiveness and the evaluation about 3D OSEM reconfiguration method should be additionally made through experiments after this.

• The Journal of Korea Robotics Society
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• v.19 no.2
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• pp.188-195
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• 2024

This paper proposes a photorealistic real-time dense 3D mapping system that utilizes a neural network-based image enhancement method and mesh-based map representation. Due to the characteristics of the underwater environment, where problems such as hazing and low contrast occur, it is hard to apply conventional simultaneous localization and mapping (SLAM) methods. At the same time, the behavior of Autonomous Underwater Vehicle (AUV) is computationally constrained. In this paper, we utilize a neural network-based image enhancement method to improve pose estimation and mapping quality and apply a sliding window-based mesh expansion method to enable lightweight, fast, and photorealistic mapping. To validate our results, we utilize real-world and indoor synthetic datasets. We performed qualitative validation with the real-world dataset and quantitative validation by modeling images from the indoor synthetic dataset as underwater scenes.

• Journal of Urban Science
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• v.7 no.2
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• pp.53-60
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• 2018

Digital Twin is a technology that creates a photocopy of real-world objects on a computer and analyzes the past and present operational status by fusing the structure, context, and operation of various physical systems with property information, and predicts the future society's countermeasures. In particular, 3D rendering technology (UAS, LiDAR, GNSS, etc.) is a core technology in digital twin. so, the research and application are actively performed in the industry in recent years. However, UAS (Unmanned Aerial System) and LiDAR (Light Detection And Ranging) have to be solved by compensating blind spot which is not reconstructed according to the object shape. In addition, the terrestrial LiDAR can acquire the point cloud of the object more precisely and quickly at a short distance, but a blind spot is generated at the upper part of the object, thereby imposing restrictions on the forward digital twin modeling. The UAS is capable of modeling a specific range of objects with high accuracy by using high resolution images at low altitudes, and has the advantage of generating a high density point group based on SfM (Structure-from-Motion) image analysis technology. However, It is relatively far from the target LiDAR than the terrestrial LiDAR, and it takes time to analyze the image. In particular, it is necessary to reduce the accuracy of the side part and compensate the blind spot. By re-optimizing it after fusion with UAS and Terrestrial LiDAR, the residual error of each modeling method was compensated and the mutual correction result was obtained. The accuracy of fusion-based 3D model is less than 1cm and it is expected to be useful for digital twin construction.

• Journal of KIISE:Software and Applications
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• v.28 no.7
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• pp.501-510
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• 2001

Generally, it is essential to estimate exact disparity for the 3D modeling from stereo images. Because existing methods calculate disparities from a whole image, they require too much cimputational time and bring about the mismatching problem. In this article, using the characteristic that the disparity vectors in stereo images are distributed not equally in a whole image but only exist about the background and obhect, we do a wavelet transformation on stereo images and estimate coarse disparity fields from the reduced lowpass field using area-based method at first-step. From these coarse disparity vectors, we generate disparity histogram and then separate object from background area using it. Afterwards, we restore only object area to the original image and estimate dense and accurate disparity by our two-step pixel-based method which does not use pixel brightness but use second gradient. We also extract feature points from the separated object area and estimate depth information by applying disparity vectors and camera parameters. Finally, we generate 3D model using both feature points and their z coordinates. By using our proposed, we can considerably reduce the computation time and estimate the precise disparity through the additional pixel-based method using LOG filter. Furthermore, our proposed foreground/background method can solve the mismatching problem of existing Delaunay triangulation and generate accurate 3D model.

• Land and Housing Review
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• v.11 no.3
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• pp.93-101
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• 2020

Recently, as a BIM-based construction simulation system, 4D CAD tools using virtual reality (VR) objects are being applied in construction project. In such a system, since the expression of the object is based on VR image, it has a sense of separation from the real environment, thus limiting the use of field engineers. For this reason, there are increasing cases of applying augmented reality (AR) technology to reduce the sense of separation from the field and express realistic VR objects. This study attempts to develop a methodology and BIM module for the pre-construction verification system using AR technology to increase the practical utility of VR-based BIM objects. To this end, authors develop an AR-based drawing verification function and drawing object-based 4D model augmentation function that can increase the practical utility of 2D drawings, and verify the applicability of the system by performing case analysis. Since VR object-based image has a problem of low realism to field engineers, the linking technology between AR object and 4D model is expected to contribute to the expansion of the use of 4D CADsystem in the construction project.

• Journal of Digital Contents Society
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• v.18 no.4
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• pp.723-731
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• 2017

The restoration of archaeological data was carried out using photographs and drawings left as past records. It can be divided into ruins and artifacts. The restoration of the ruins was performed by modeling the individual parts and parts left by the photographs, aligning them and synthesizing them, and reconstructing them three-dimensionally as one object. Restoration of artifacts was performed on both photographs and drawings. After the modeling work is prioritized through the photographs, there is a method of restoring the original image by modifying the texture image of the damaged part of the modeled artifact, or restoring the original image by modeling and synthesizing the deleted part in the artifact. The restoration of the artifacts through the drawings was carried out by three - dimensional modeling and reconstruction through real mapping of images. The reconstructed archaeological data can be used in various directions. In particular, it is possible to verify and compare the results of the numerical analysis and interpretation of the past 2D data, and to provide a more accurate analysis plan in the future.

• The Journal of Korea Robotics Society
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• v.3 no.1
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• pp.33-41
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• 2008

Based on object recognition technology, we present a new global localization method for robot navigation. For doing this, we model any indoor environment using the following visual cues with a stereo camera; view-based image features for object recognition and those 3D positions for object pose estimation. Also, we use the depth information at the horizontal centerline in image where optical axis passes through, which is similar to the data of the 2D laser range finder. Therefore, we can build a hybrid local node for a topological map that is composed of an indoor environment metric map and an object location map. Based on such modeling, we suggest a coarse-to-fine strategy for estimating the global localization of a mobile robot. The coarse pose is obtained by means of object recognition and SVD based least-squares fitting, and then its refined pose is estimated with a particle filtering algorithm. With real experiments, we show that the proposed method can be an effective vision- based global localization algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.2A
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• pp.137-145
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• 2002

In the method of 3D modeling, stereo matching method which obtains three dimensional depth information from the two images is taken from the different view points. In general, it is very essential work for the 3D modeling from 2D stereo images to estimate the exact disparity through fading the conjugate pair of pixel from the left and right image. In this paper to solve the problems of the stereo image disparity estimation, we introduce a novel approach method to improve the exactness and efficiency of the disparity. In the first place, we perform a wavelet transformation of the stereo images and set the reference points in the image by the feature-based matching method. This reference points have very high probability over 95 %. In the base of these reference points we can decide the size of the variable block searching windows for estimating dense disparity of area based method and perform the ordering constraint to prevent mismatching. By doing this, we could estimate the disparity in a short time and solve the occlusion caused by applying the fried-sized windows and probable error caused by repeating patterns.

• Journal of KIISE:Databases
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• v.29 no.2
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• pp.110-118
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• 2002

This paper presents a 3-D graphic database system based on XML that supports content-based retrievals of 3-D images, Most of graphics application systems are currently centered around the processing of 2-D images and research works on 3-D graphics are mainly concerned about the visualization aspects of 3-D image. They do not support the semantic modeling of 3-D objects and their spatial relations. In our data model, 3-D images are represented as compositions of 3-D graphic objects with associated spatial relations. Complex 3-D objects are mode]ed using a set of primitive 3-D objects rather than the lines and polygons that are found in traditional graphic systems. This model supports content-based retrievals of scenes containing a particular object or those satisfying certain spatial relations among the objects contained in them. 3-D images are stored in the database as XML documents using 3DGML DTD that are developed for modeling 3-D graphic data. Finally, this paper describes some examples of query executed in our Web-based prototype database system.