• The Journal of the Acoustical Society of Korea
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• v.30 no.1
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• pp.22-32
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• 2011

The present study examined the effects of the complexity of the 3D models on the results of acoustic simulation which is the predominant tool of the acoustical design of buildings. Also, the effects of the 3D model on the auralized sounds were investigated. In order to carry out the study, four 3D models with different levels of complexity were introduced for a real auditorium which have different numbers of surfaces in the persuit of the guidance of odeon room acoustic software. The set-up of models was also based on the level of transition order of the program. And the acoustic experiments were performed measuring room acoustic parameters including SPL, RT, C80, D50. Acoustic computer simulations were performed using four different models. Then, the results of the computer modeling were compared with the measured acoustical parameters. In addition, sound sources were recorded in the field and auralized sounds were made in convolution with the impulse source made from acoustic modeling. Then, subjective tests were undertaken using auralized sounds. As the results, it was found that the result of the acoustic simulation were closer to the real room acoustic properties when 3D model was more particularly made. For the subjective test, the listening materials were acknowledged as similar with the real sound source when more complex 3D model was used. Then, it could be concluded that the complexity of the 3D model affects the results of the acoustic modeling as well as subjective tests.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.4
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• pp.41-48
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• 2008

Currently used 3D models, which are mostly focused on visualization of 3D objects and lack topological structure, have limitation in being used for 3D spatial analyses and applications. However, implementing a full topology for the indoor spatial objects is less practical due to the increase of complexity and computation time. This study suggests an alternative method to build a 3D indoor model with less complexity using a spatial DBMS. Storing spatial and nonspatial information of indoor spaces in DB tables enables faster queries, computation and analyses. Also it is possible to display them in 2D or 3D using the queried information. This study suggests a 2D-3D hybrid data model, which combines the 2D topology constructed from CAD floor plans and stored in a spatial DBMS and the 3D visualization functionality. This study showed the process to build the proposed model in a spatial DBMS and use spatial functions and queries to visualize in 2D and 3D. And, then, as an example application, it illustrated the process to build an indoor evacuation simulator.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.1
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• pp.228-246
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• 2011

A 3D model based approach for a face representation and recognition algorithm has been investigated as a robust solution for pose and illumination variation. Since a generative 3D face model consists of a large number of vertices, a 3D model based face recognition system is generally inefficient in computation time and complexity. In this paper, we propose a novel 3D face representation algorithm based on a pixel to vertex map (PVM) to optimize the number of vertices. We explore shape and texture coefficient vectors of the 3D model by fitting it to an input face using inverse compositional image alignment (ICIA) to evaluate face recognition performance. Experimental results show that the proposed face representation and recognition algorithm is efficient in computation time while maintaining reasonable accuracy.

• Structural Engineering and Mechanics
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• v.84 no.3
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• pp.323-335
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• 2022

The main idea of the framework is to seamlessly combine a reasonably accurate and fast surrogate model with the importance sampling strategy. Developing a surrogate model for predicting structures' dynamic responses is challenging because it involves high-dimensional inputs and outputs. For this purpose, a novel surrogate model based on cutting-edge deep learning architectures specialized for capturing temporal relationships within time-series data, namely Long-Short term memory layer and Transformer layer, is designed. After being properly trained, the surrogate model could be utilized in place of the finite element method to evaluate structures' responses without requiring any specialized software. On the other hand, the importance sampling is adopted to reduce the number of calculations required when computing the failure probability by drawing more relevant samples near critical areas. Thanks to the portability of the trained surrogate model, one can integrate the latter with the Importance sampling in a straightforward fashion, forming an efficient framework called TTIS, which represents double advantages: less number of calculations is needed, and the computational time of each calculation is significantly reduced. The proposed approach's applicability and efficiency are demonstrated through three examples with increasing complexity, involving a 1D beam, a 2D frame, and a 3D building structure. The results show that compared to the conventional Monte Carlo simulation, the proposed method can provide highly similar reliability results with a reduction of up to four orders of magnitudes in time complexity.

• Proceedings of the IEEK Conference
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• summer
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• pp.137-142
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• 2004

In this paper, we propose a new scheme for geometry coding of three-dimensional (3-D) mesh models using a fixed spectral basis. In order to code the mesh geometry information, we generate a fixed spectral basis using the dual graph derived from the 3-D mesh topology. After we partition a 3-D mesh model into several independent sub-meshes to reduce coding complexity, the mesh geometry information is projected onto the generated orthonormal bases which are the eigenvectors of the Laplacian matrix of the 3-D mesh. Finally, spectral coefficients are coded by a quantizer and a variable length coder. The proposed scheme can not only overcome difficulty of generating a fixed spectral basis, but also reduce coding complexity. Moreover, we can provide an efficient multi-resolution representation of 3-D meshes.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.4
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• pp.31-38
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• 2009

Most 3D models found in the literature focus on theoretical topology for exterior 3D volumes. Although there are a few indoor models such as CityGML or IFC, implementing a full topology for the indoor spaces is either less practical due to the complexity or not even necessary in some application domains. Moreover, current spatial DBMSs do not support functionalities explicitly for 3D topological relations. In this study, an alternative method to build a 3D indoor model with less complexity ernativespatial DBMS is suggested. Focusnation the fact that semantic attributes can be storedion the floor surface, we suggestivemulti-layered 3D model for indoor spaces. We show the process to build the proposed model in the PostGIS, a spatial DBMS. And, then, as an example application, we illustrate the process to build and run a campus building information system.

• 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.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.9
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• pp.84-101
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• 1997

Inferring and recognizing 3D objects form a 2D occuluded image has been an important research area of computer vision. The octree model, a hierarchical volume description of 3D objects, may be utilized to generate projected images from arbitrary viewing directions, thereby providing an efficient means of the data base for 3D object recognition. We present a fast algorithm of finding the 4 pairs of feature points to estimate the viewing direction. The method is based on matching the object contour to the reference occuluded shapes of 49 viewing directions. The initially best matched viewing direction is calibrated by searching for the 4 pairs of feature points between the input image and the image projected along the estimated viewing direction. Then the input shape is recognized by matching to the projectd shape. The computational complexity of the proposed method is shown to be O(n$^{2}$) in the worst case, and that of the simple combinatorial method is O(m$^{4}$.n$^{4}$) where m and n denote the number of feature points of the 3D model object and the 2D object respectively.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.500-503
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• 1997

In this paper, a method for recognizing 3-D objects using the 3-D Hough transform and the robust stereo vision is studied. A 3-D object is recognized through two steps; modeling step and matching step. In modeling step, features of the object are extracted by analyzing the IGES file. In matching step, the values of the sensed image are compared with those of the IGES file which is assumed to location and orientation in the 3-D Hough transform domain. Since we use the 3-D Hough transform domain of the input image directly, the sensitivity to the noise and the high computational complexity could be significantly allcv~ated. Also, the cost efficiency is improved using the robust stereo vision for obtaining depth map image which is needed for 3-D Hough transform. In order lo verify the proposed method, real telephone model is recognized. Thc results of the location and orientation of the model are presented.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.24 no.1
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• pp.1-9
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• 2016

In this paper, we integrate three degree of freedom(3DOF) point-mass model for aircraft and three-dimensional path generation algorithms using dubins curve and nonlinear path tracking law. Through this integration, we apply the path generation algorithm to the path planning, and verify tracking performance and feasibility of using the aircraft 3DOF point-mass model for air traffic management. The accuracy of modeling 6DOF aircraft is more accurate than that of 3DOF model, but the complexity of the calculation would be raised, in turn the rate of computation is more likely to be slow due to the increase of degree of freedom. These obstacles make the 6DOF model difficult to be applied to simulation requiring real-time path planning. Therefore, the 3DOF point-mass model is also sufficient for simulation, and real-time path planning is possible because complexity can be reduced, compared to those of the 6DOF. Dubins curve used for generating the optimal path has advantage of being directly available to apply path planning. However, we use the algorithm which extends 2D path to 3D path since dubins curve handles the two dimensional path problems. Control law for the path tracking uses the nonlinear path tracking laws. Then we present these concomitant simulation results.