• The KIPS Transactions:PartA
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• v.13A no.4 s.101
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• pp.305-316
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• 2006

Current rendering processors are organized mainly to process a triangle as fast as possible and recently parallel 3D rendering processors, which can process multiple triangles in parallel with multiple rasterizers, begin to appear. For high performance in processing triangles, it is desirable for each rasterizer have its own local pixel cache. However, the consistency problem may occur in accessing the data at the same address simultaneously by more than one rasterizer. In this paper, we propose a parallel rendering processor architecture resolving such consistency problem effectively. Moreover, the proposed architecture reduces the latency due to a pixel cache miss significantly. For the above two goals, effective memory organizations including a new pixel cache architecture are presented. The experimental results show that the proposed architecture achieves almost linear speedup at best case even in sixteen rasterizers.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.1
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• pp.46-55
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• 2007

The Newton-Raphson's algorithm for finding a floating point reciprocal and inverse square root calculates the result by performing a fixed number of multiplications. In this paper, an improved Newton-Raphson's algorithm is proposed, that performs multiplications a variable number. Since the number of multiplications performed by the proposed algorithm is dependent on the input values, the average number of multiplications per an operation is derived from many reciprocal and inverse square tables with varying sizes. The superiority of this algorithm is proved by comparing this average number with the fixed number of multiplications of the conventional algorithm. Since the proposed algorithm only performs the multiplications until the error gets smaller than a given value, it can be used to improve the performance of a reciprocal and inverse square root unit. Also, it can be used to construct optimized approximate tables. The results of this paper can be applied to many areas that utilize floating point numbers, such as digital signal processing, computer graphics, multimedia, scientific computing, etc.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.5
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• pp.17-25
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• 2019

In this paper, we introduce the technology to convert a single human image into a fashion show animation video clip. The technology can help the customers confirm the dynamic fitting result when combined with the virtual try on technique as well as the interesting experience to a normal person of being a fashion model. We developed an extended technique of full human 2D to 3D inverse modeling based on SMPLify human body inverse modeling technique, and a rigged model animation method. The 3D shape deformation of the full human from the body model was performed by 2 part deformation in the image domain and reconstruction using the estimated depth information. The quality of resultant animation videos are made to be publically available for evaluation. We consider it is a promising approach for commercial application when supplemented with the post - processing technology such as image segmentation technique, mapping technique and restoration technique of obscured area.

• Structural Engineering and Mechanics
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• v.7 no.6
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• pp.589-599
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• 1999

This paper presents the development and applications of the software package JIFEX, a new finite element system which can be used for structural analysis and optimum design by the modern computer hardware and software technologies such as MS Windows95/NT and Pentium PC platforms. The complete system of JIFEX is programmed with $C/C^{++}$ language to make full use of advanced facilities of MS Windows95/NT. In the system, the finite element data pre-processing, based on the most popular CAD package AutoCAD (R13, R14), has been implemented, so that the finite element modeling could be integrated with geometric modeling of CAD. The system not only has interactive graphics facility for data post-processing, but also realizes the real-time computing visualization by means of the Dynamic Data Exchange (DDE) technique. Running on the Pentium computers, JIFEX can solve large-scale finite element analysis problems such as the ones with more than 60000 nodes in the finite element model.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.664-670
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• 2018

In modern society, CCTV, which is the eye of surveillance, is being used to collect image data in various ways in daily life. CCTV is used not only for security, surveillance, and crime prevention but also in many fields such as automobile and black box. In this paper, we have developed a STM32F407 ARM chip based camera system for various applications. In order to develop camera system, modeling of camera system based on 3D structure was carried out in SolidWorks environment. The PCB board design was developed to extract the PCB parts from the camera system modeling files into iges files, convert them from the Altium Designer tool into 3D and 2D boards, After designing the camera system circuit and PCB, we have been studying the implementation of the stable system by using TRM (Thermal Risk Management) tool to cope with the heat simulation generated on the board.

• The Journal of the Convergence on Culture Technology
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• v.4 no.4
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• pp.373-377
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• 2018

In this paper, we propose an implementation of a neural network accelerator for reducing the rendering noise using OpenCL. Among the rendering algorithms, we selects a ray tracing to assure a high quality graphics. Ray tracing rendering uses ray to render, less use of the ray will result in noise. Ray used more will produce a higher quality image but will take operation time longer. To reduce operation time whiles using fewer rays, Learning Base Filtering algorithm using neural network was applied. it's not always produce optimize result. In this paper, a new approach to Matrix Multiplication that is based on General Matrix Multiplication for improved performance. The development environment, we used specialized in high speed parallel processing of OpenCL. The proposed architecture was verified using Kintex UltraScale XKU6909T-2FDFG1157C FPGA board. The time it takes to calculate the parameters is about 1.12 times fast than that of Verilog-HDL structure.

• International journal of advanced smart convergence
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• v.10 no.2
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• pp.108-122
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• 2021

With the development of 3D graphics software and the speed of computer hardware, it is an era that can be realistically expressed not only in movie visual effects but also in console games. In the production of such realistic 3D models, 3D scans are increasingly used because they can obtain hyper-realistic results with relatively little effort. Among the various 3D scanning methods, photogrammetry can be used only with a camera. Therefore, no additional hardware is required, so its demand is rapidly increasing. Most 3D artists shoot as many images as possible with a video camera, etc., and then calculate using all of those images. Therefore, the photogrammetry method is recognized as a task that requires a lot of memory and long hardware operation. However, research on how to obtain precise results with 3D photogrammetry scans is insufficient, and a large number of photos is being utilized, which leads to increased production time and data capacity and decreased productivity. In this study, point cloud data generated according to changes in the number and resolution of photographic images were produced, and an experiment was conducted to compare them with original data. Then, the precision was measured using the average distance value and standard deviation of each vertex of the point cloud. By comparing and analyzing the difference in the precision of the 3D photogrammetry scans according to the number and resolution of images, this paper presents a direction for obtaining the most precise and effective results to 3D artists.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.10-16
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• 2022

As an important part of virtual production, In-camera VFX is the process of shooting actual objects and virtual three-dimensional backgrounds in real-time through computer graphics technology and display technology, and obtaining the final film. In the In-camera VFX process, there are currently only two types of medium used to undertake background imaging, LED wall and chroma key screen. Among them, the In-camera VFX based on LED wall realizes background imaging through LED display technology. Although the imaging quality is guaranteed, the high cost of LED wall increases the cost of virtual production. The In-camera VFX based on chroma key screen, the background imaging is realized by real-time keying technology. Although the price is low, due to the limitation of real-time keying technology and lighting conditions, the usability of the final picture is not high. The short-throw projection technology can compress the projection distance to within 1 meter and get a relatively large picture, which solves the problem of traditional projection technology that must leaving a certain space between screen and the projector, and its price is relatively cheap compared to the LED wall. Therefore, in the In-camera VFX process, short-throw projection technology can be tried to project backgrounds. This paper will analyze the principle of short-throw projection technology and the existing In-camera VFX solutions, and through the comparison experiments, propose a low-cost solution that uses short-throw projectors to project virtual backgrounds and realize the In-camera VFX process.

• Journal of Industrial Convergence
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• v.19 no.6
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• pp.49-57
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• 2021

Digital Signage and multi-view image system are used as the 4th media to deliver stories and information due to their strong immersion. A content image displayed on large Digital Signage is produced with the use of computer graphics, rather than reality image. That is because the images shot for content making have an extremely limited range of production and their limitation to high resolution, and thereby have difficulty being displayed in a large and wide Digital Signage screen. In case of Screen X and Escape that employ the left and right walls of in the center a movie theater as a screen, images are shot with three cameras for Digital Cinema, and are screened in a cinema with multi-view image system after stitching work is applied. Such realistic images help viewers experience real-life content. This research will be able to display high-resolution images on Digital Signage without quality degradation by using the multi-view image making technique of Screen X and Chroma key technique are showed the high-resolution Digital Signage content making method.

• Smart Structures and Systems
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• v.29 no.1
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• pp.237-250
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• 2022

Structural health monitoring (SHM) plays an important role in ensuring the safety and functionality of critical civil infrastructure. In recent years, numerous researchers have conducted studies to develop computer vision and machine learning techniques for SHM purposes, offering the potential to reduce the laborious nature and improve the effectiveness of field inspections. However, high-quality vision data from various types of damaged structures is relatively difficult to obtain, because of the rare occurrence of damaged structures. The lack of data is particularly acute for fatigue crack in steel bridge girder. As a result, the lack of data for training purposes is one of the main issues that hinders wider application of these powerful techniques for SHM. To address this problem, the use of synthetic data is proposed in this article to augment real-world datasets used for training neural networks that can identify fatigue cracks in steel structures. First, random textures representing the surface of steel structures with fatigue cracks are created and mapped onto a 3D graphics model. Subsequently, this model is used to generate synthetic images for various lighting conditions and camera angles. A fully convolutional network is then trained for two cases: (1) using only real-word data, and (2) using both synthetic and real-word data. By employing synthetic data augmentation in the training process, the crack identification performance of the neural network for the test dataset is seen to improve from 35% to 40% and 49% to 62% for intersection over union (IoU) and precision, respectively, demonstrating the efficacy of the proposed approach.