• Advances in Computational Design
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• v.4 no.2
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• pp.155-177
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• 2019

Operation and Maintenance (O&M) phase is the main contributor to the total lifecycle cost of a building. Previous studies have described that Building Information Models (BIM), if available with detailed asset information and their properties, can enable rapid troubleshooting and execution of O&M tasks by providing the required information of the facility. Despite the potential benefits, there is still rarely BIM with Mechanical, Electrical and Plumbing (MEP) assets and properties that are available for O&M. BIM is usually not in possession for existing buildings and generating BIM manually is a time-consuming process. Hence, there is a need for an automated approach that can reconstruct the MEP systems in BIM. Previous studies investigated automatic reconstruction of BIM using architectural drawings, structural drawings, or the combination with photos. But most of the previous studies are limited to reconstruct the architectural and structural components. Note that mechanical components in the building typically require more frequent maintenance than architectural or structural components. However, the building mechanical drawings are relatively more complex due to various type of symbols that are used to represent the mechanical systems. In order to address this challenge, this paper proposed a symbol recognition framework that can automatically recognize the different type of symbols in the building mechanical drawings. This study applied vector-based computer vision techniques to recognize the symbols and their properties (e.g., location, type, etc.) in two vector-based input documents: 2D drawings and the symbol description document. The framework not only enables recognizing and locating the mechanical component of interest for BIM reconstruction purpose but opens the possibility of merging the updated information into the current BIM in the future reducing the time of repeated manual creation of BIM after every renovation project.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.6
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• pp.445-451
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• 2021

Due to the recent spread and increasing damage of COVID-19, the most important measure to prevent infection is to find infected people early. Group testing which introduced half a century ago, can be used as a diagnostic method for COVID-19 and has become very efficient method. In this paper, we review the fundamental principles of existing group testing algorithms. In addition, the sparse signal reconstruction approach proposed by compressed sensing is improved and presented as a solution to group testing. Compressed sensing and group testing differ in computational methods, but are similar in that they find sparse signals. The our simulation results show the superiority of the proposed sparse signal reconstruction method. It is noteworthy that the proposed method shows performance improvement over other algorithms in the group testing schemes. It also shows performance improvement when finding a large number of defective samples.

• Journal of Korea Multimedia Society
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• v.12 no.2
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• pp.209-218
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• 2009

3D backprojection is a kind of reconstruction algorithm to generate volume data consisting of tomographic images, which provides spatial information of the original 3D data from hundreds of 2D projections. The computational time of backprojection increases in proportion to the size of volume data and the number of projection images since the value of every voxel in volume data is calculated by considering corresponding pixels from hundreds of projections. For the reduction of computational time, fast GPU based 3D backprojection methods have been studied recently and the performance of them has been improved significantly. This paper presents two multiple GPU based methods to maximize the parallelism of GPU and compares the efficiencies of two methods by considering both the number of projections and the size of volume data. The first method is to generate partial volume data independently for all projections after allocating a half size of volume data on each GPU. The second method is to acquire the entire volume data by merging the incomplete volume data of each GPU on CPU. The in-complete volume data is generated using the half size of projections after allocating the full size of volume data on each GPU. In experimental results, the first method performed better than the second method when the entire volume data can be allocated on GPU. Otherwise, the second method was efficient than the first one.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.1
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• pp.97-107
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• 2002

In this paper, we propose the realization of on-line handwritten Chinese character recognition for mobile personal digital assistants (PDA). We focus on the development of an algorithm having a high recognition performance under the restriction that PDA requires small memory storage and less computational complexity in comparison with PC. Therefore, we use index matching method having computational advantage for fast recognition and we suggest a unit reconstruction method to minimize the memory size to store the character models and to accomodate the various changes in stroke order and stroke number of each person in handwriting Chinese characters. We set up standard model consisting of 1800 characters using a set of pre-defined units. Input data are measured by similarity among candidate characters selected on the basis of stroke numbers and region features after preprocessing and feature extracting. We consider 1800 Chinese characters adopted in the middle and high school in Korea. We take character sets of five person, written in printed style, irrespective of stroke ordering and stroke numbers. As experimental results, we obtained an average recognition time of 0.16 second per character and the successful recognition rate of 94.3% with MIPS R4000 CPU in PDA.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.3 s.303
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• pp.39-52
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• 2005

In this paper, a registration method is presented to register partial 3D point clouds, acquired from a multi-view camera, for 3D reconstruction of an indoor environment. In general, conventional registration methods require a high computational complexity and much time for registration. Moreover, these methods are not robust for 3D point cloud which has comparatively low precision. To overcome these drawbacks, a projection-based registration method is proposed. First, depth images are refined based on temporal property by excluding 3D points with a large variation, and spatial property by filling up holes referring neighboring 3D points. Second, 3D point clouds acquired from two views are projected onto the same image plane, and two-step integer mapping is applied to enable modified KLT (Kanade-Lucas-Tomasi) to find correspondences. Then, fine registration is carried out through minimizing distance errors based on adaptive search range. Finally, we calculate a final color referring colors of corresponding points and reconstruct an indoor environment by applying the above procedure to consecutive scenes. The proposed method not only reduces computational complexity by searching for correspondences on a 2D image plane, but also enables effective registration even for 3D points which have low precision. Furthermore, only a few color and depth images are needed to reconstruct an indoor environment.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.4
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• pp.249-256
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• 2019

This paper presents an optimization framework of electrical impedance tomography for characterizing electrical conductivity profiles of concrete structures in two dimensions. The framework utilizes a partial-differential-equation(PDE)-constrained optimization approach that can obtain the spatial distribution of electrical conductivity using measured electrical potentials from several electrodes located on the boundary of the concrete domain. The forward problem is formulated based on a complete electrode model(CEM) for the electrical potential of a medium due to current input. The CEM consists of a Laplace equation for electrical potential and boundary conditions to represent the current inputs to the electrodes on the surface. To validate the forward solution, electrical potential calculated by the finite element method is compared with that obtained using TCAD software. The PDE-constrained optimization approach seeks the optimal values of electrical conductivity on the domain of investigation while minimizing the Lagrangian function. The Lagrangian consists of least-squares objective functional and regularization terms augmented by the weak imposition of the governing equation and boundary conditions via Lagrange multipliers. Enforcing the stationarity of the Lagrangian leads to the Karush-Kuhn-Tucker condition to obtain an optimal solution for electrical conductivity within the target medium. Numerical inversion results are reported showing the reconstruction of the electrical conductivity profile of a concrete specimen in two dimensions.

• Journal of KIISE:Software and Applications
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• v.35 no.12
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• pp.789-799
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• 2008

For the communication between human and computer in an interactive computing environment, the gesture recognition has been studied vigorously. The algorithms which use the 2D features for the feature extraction and the feature comparison are faster, but there are some environmental limitations for the accurate recognition. The algorithms which use the 2.5D features provide higher accuracy than 2D features, but these are influenced by rotation of objects. And the algorithms which use the 3D features are slow for the recognition, because these algorithms need the 3d object reconstruction as the preprocessing for the feature extraction. In this paper, we propose a method to extract the 3D features combined with the 3D object reconstruction in real-time. This method generates three kinds of 3D projection maps using the modified GPU-based visual hull generation algorithm. This process only executes data generation parts only for the gesture recognition and calculates the Hu-moment which is corresponding to each projection map. In the section of experimental results, we compare the computational time of the proposed method with the previous methods. And the result shows that the proposed method can apply to real time gesture recognition environment.

• Journal of the HCI Society of Korea
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• v.1 no.1
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• pp.53-61
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• 2006

In this paper, we propose a novel method for 3D reconstruction of an indoor scene using a multi-view camera. Until now, numerous disparity estimation algorithms have been developed with their own pros and cons. Thus, we may be given various sorts of depth images. In this paper, we deal with the generation of a 3D surface using several 3D point clouds acquired from a generic multi-view camera. Firstly, a 3D point cloud is estimated based on spatio-temporal property of several 3D point clouds. Secondly, the evaluated 3D point clouds, acquired from two viewpoints, are projected onto the same image plane to find correspondences, and registration is conducted through minimizing errors. Finally, a surface is created by fine-tuning 3D coordinates of point clouds, acquired from several viewpoints. The proposed method reduces the computational complexity by searching for corresponding points in 2D image plane, and is carried out effectively even if the precision of 3D point cloud is relatively low by exploiting the correlation with the neighborhood. Furthermore, it is possible to reconstruct an indoor environment by depth and color images on several position by using the multi-view camera. The reconstructed model can be adopted for interaction with as well as navigation in a virtual environment, and Mediated Reality (MR) applications.

• Journal of the Korean Society for Marine Environment & Energy
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• v.15 no.4
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• pp.273-280
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• 2012

The numerical simulation using the Lattice Boltzmann Method in the field of computational fluid dynamics becomes wider in the engineering applications because of its simplicity of update rules compared to the conventional Navier-Stokes solvers. Here, a two-dimensional D2Q9 LB model is numerically tested with a few new computational treatment on the free surface. The single relaxation time is applied under the gravitational field where applied only in the higher density fluid because of its big density difference. At the free surface, the reconstruction techniques in combination with boundary conditions is adopted in order to get some distribution function coming into the fluid site from the air one, and surface tension, early stable test for the gravitional field is considered in it. With the implementation of the gravitational profile, conserving the overall mass and grid dependency are observed during the calculations and freesurface advance track is well captured with an experiment.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.14 no.4
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• pp.525-535
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• 2001

In this paper, a new adaptive analysis scheme for element-free Galerkin method(EFGM) is proposed. The novel point of this scheme is that the triangular cell structure based on the Delaunay triangulation is used in the numerical integration and the node adding/removing process. In adaptive analysis with this scheme, there is no need to divide the integration cell and the memory cell structure. For the adaptive analysis of crack propagation, the reconstruction of cell structure by adding and removing the nodes on integration cells based the estimated error should be carried out at every iteration step by the Delaunay triangulation technique. This feature provides more convenient user interface that is closer to the real mesh-free nature of EFGM. The analysis error is obtained basically by calculating the difference between the values of the projected stresses and the original EFG stresses. To evaluate the performance of proposed adaptive procedure, the crack propagation behavior is investigated for several examples.