• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권6호
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• pp.2782-2805
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• 2018

We present a legorization framework that produces a LEGO model from user-specified 3D mesh model. Our framework is composed of two stages: voxelization and legorization. In the voxelization, input 3D mesh is converted to a voxel model. To preserve the shape of the 3D mesh, we devise a silhouette fitting process for the initial voxel model. For legorization, we propose three objectives: stability, aesthetics and efficiency. These objectives are expressed in a tiling equation, which builds a LEGO model using layer-by-layer approach. We legorize five models including characters and buildings to prove the excellence of our framework.

• Proceedings of the Korean Society of Computer Information Conference
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• 한국컴퓨터정보학회 2023년도 제67차 동계학술대회논문집 31권1호
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• pp.323-324
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• 2023

본 논문에서는 다양한 복원 인공지능 알고리즘 중 하나인 3차원 복원 기술은 실제로 존재하는 물체의 2차원적인 픽셀을 3차원의 형태로 구현하여 형상화한다. 정확한 3차원 정보 처리가 요구됨에 따라 포인트 클라우드로 표현되는 데이터를 통해 정확한 쿨체의 크기 정보나 좌표 정보를 표시할 수 있다. 데이터의 픽셀을 분석하여 3차원의 형태로 구현할 것을 정의하는 복셀화(Voxelization) 알고리즘 전처리 과정을 통해 3차원 복원 기술 3D-GAN 활용으로 3차원 형태 형상화를 하였다. 본 논문에서는 3차원 복원 알고리즘 통하여 2차원 포인트 클라우드를 분석해 3차원 형태로 복원하는 기술에 대한 설명한다.

• Journal of Korea Multimedia Society
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• 제18권10호
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• pp.1157-1163
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• 2015

In this paper, we propose a registration method of 3d facial scan data and CBCT data using voxelization and distance map. First, two data sets are initially aligned by exploiting the voxelization of 3D facial scan data and the information of the center of mass. Second, a skin surface is extracted from 3D CBCT data by segmenting air and skin regions. Third, the positional and rotational differences between two images are accurately aligned by performing the rigid registration for the distance minimization of two skin surfaces. Experimental results showed that proposed registration method correctly aligned 3D facial scan data and CBCT data for ten patients. Our registration method might give useful clinical information for the oral surgery planning and the diagnosis of the treatment effects after an oral surgery.

• Journal of Korea Multimedia Society
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• 제18권2호
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• pp.113-119
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• 2015

This paper suggests an efficient method for making the high resolution volexlized model from a polygonal surface object. A distinctive strength of the method is that a surface model, however complex one, can be transformed and formed an absolute voxelized solid model in a various resolution. It caused by producing a voxel by integrating the informations for the candidated voxels separately detected in each 3D-axial direction. This method reduces memory complexity by storing the information of voxels that is produced during the 2-phase volxelization(surface and inner voxelization) of a surface object in a binary file. For the computational efficiency, a parallel process using multi-threads is applied in the process of the inner voxelization, it also takes advantage of time complexity.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 대한산업공학회/한국경영과학회 2002년도 춘계공동학술대회
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• pp.266-271
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• 2002

We propose a hardware accelerated voxelization method for various 3D object model such as surface models, solid models, and volumetric CSG models. The algorithm utilizes the stencil buffer that is one of modern Open히 graphics hardware features. The stencil buffer is originally used to restrict drawing to certain portions of the screen. The volumetric representations of given 3D objects are constructed slice-by-slice. For each slice, the algorithm restricts the drawing areas constructed inner region of 3D objects using the stencil buffer, and generates slices of the volumetric representation for target objects. As a result, we can provide volume graphics support for various engineering applications such as multi-axis machining simulation, collision detection and finite element analysis.

• Nuclear Engineering and Technology
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• 제55권6호
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• pp.1966-1973
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• 2023

Virtual reality technology has been widely used in the field of nuclear and radiation safety, dose rate computing in virtual environment is essential for optimizing radiation protection and planning the work in radioactive-controlled area. Because the CPU-based gamma dose rate computing takes up a large amount of time and computing power for voxelization of volumetric radioactive source, it is inefficient and limited in its applied scope. This study is to develop an efficient gamma dose rate computing code and apply into fast virtual simulation. To improve the computing efficiency of the point kernel algorithm in the reference (Li et al., 2020), we design a GPU-based computing framework for taking full advantage of computing power of virtual engine, propose a novel voxelization algorithm of volumetric radioactive source. According to the framework, we develop the GPPK(GPU-based point kernel gamma dose rate computing) code using GPU programming, to realize the fast dose rate computing in virtual world. The test results show that the GPPK code is play and plug for different scenarios of virtual simulation, has a better performance than CPU-based gamma dose rate computing code, especially on the voxelization of three-dimensional (3D) model. The accuracy of dose rates from the proposed method is in the acceptable range.

• Journal of the Korean Society for Precision Engineering
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• 제13권6호
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• pp.90-101
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• 1996

Determination of assembly sequence of components is a key issue in assembly operation. Although a number of articles dealing with assembly sequence determination have appeared, an efficient and general methodology for complex products has yet to appear. The objective of this paper is to present the problems and models used to generate assembly sequence from design data. An essential idea of this research is to acquire a finite number of voxels from any complex geometric entity, such as 3D planar polygons, hollow spheres, cylinders. cones, tori, etc. In order to find a feasible assembly sequence, the following four steps are needed: (1) The components composing of an assembly product are identified and then the geometric entities of each component are extracted. (2) The geometric entities extracted in the first step are translated into a number of voxels. (3) All the mating or coupling relations between components are found by considering relations between voxels. (4) The components to be disassembled are determined using CCGs (Component Coupling Graph).

• Journal of the Institute of Electronics Engineers of Korea SP
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• 제38권1호
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• pp.33-42
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• 2001

Recently, the interests in the 3D image, generated from the range data and CAD, have exceedingly increased, accordingly a various 3D image database is being constructed. The efficient and fast scheme to access the desired image data is the important issue in the application area of the Internet and digital library. However, it is difficult to manage the 3D image database because of its huge size. Therefore, a proper descriptor is necessary to manage the data efficiently, including the content-based search. In this paper, the proposed shape descriptor is based on the voxelization of the 3D image. The medial axis transform, stemming from the mathematical morphology, is performed on the voxelized 3D image and the graph, which is composed of node and edge, is generated from skeletons. The generated graph is adequate to the novel shape descriptor due to no loss of geometric information and the similarity of the insight of the human. Therefore the proposed shape descriptor would be useful for the recognition of 3D object, compression, and content-based search.

• Nuclear Engineering and Technology
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• 제55권5호
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• pp.1718-1733
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• 2023

The virtual Frisch-grid method for room-temperature radiation detectors has been widely used because of its simplicity and high performance. Recently, side electrodes were separately attached to each surface of the detectors instead of covering the entire detector surface with a single electrode. The side-electrode structure enables the measurement of the three-dimensional (3D) gamma-ray interaction in the detector. The positional information of the interaction can then be utilized to precisely calibrate the response of the detector for gamma-ray spectroscopy and imaging. In this study, we developed a 3D position-sensitive 5 × 5 × 12 mm³ cadmium-zinc-telluride (CZT) detector and applied a flattening method to correct detector responses. Collimated gamma-rays incident on the surface of the detector were scanned to evaluate the positional accuracy of the detection system. Positional distributions of the radiation interactions with the detector were imaged for quantitative and qualitative evaluation. The energy spectra of various radioisotopes were measured and improved by the detector response calibration according to the calculated positional information. The energy spectra ranged from 59.5 keV (emitted by ²⁴¹Am) to 1332 keV (emitted by ⁶⁰Co). The best energy resolution was 1.06% at 662 keV when the CZT detector was voxelized to 20 × 20 × 10.

• Journal of Advanced Navigation Technology
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• 제27권2호
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• pp.190-196
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• 2023

Recently, following the development of LIDAR technology which can detect distance from the object, the interest for LIDAR based 3D object detection network is getting higher. Previous networks generate inaccurate localization results due to spatial information loss during voxelization and downsampling. In this study, we propose an attention-based convergence method and a camera-LIDAR convergence system to acquire high-level features and high positional accuracy. First, by introducing the attention method into the Voxel-RCNN structure, which is a grid-based 3D object detection network, the multi-scale sparse 3D convolution feature is effectively fused to improve the performance of 3D object detection. Additionally, we propose the late-fusion mechanism for fusing outcomes in 3D object detection network and 2D object detection network to delete false positive. Comparative experiments with existing algorithms are performed using the KITTI data set, which is widely used in the field of autonomous driving. The proposed method showed performance improvement in both 2D object detection on BEV and 3D object detection. In particular, the precision was improved by about 0.54% for the car moderate class compared to Voxel-RCNN.