• Journal of information and communication convergence engineering
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• v.10 no.4
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• pp.411-419
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• 2012

This paper proposes a semi-automatic image-based approach for 3-dimensional (3D) modeling of buildings along streets. Image-based urban 3D modeling techniques are typically based on the use of aerial and ground-level images. The aerial image of the relevant area is extracted from publically available sources in Google Maps by stitching together different patches of the map. Panoramic images are common for ground-level recording because they have advantages for 3D modeling. A panoramic video recorder is used in the proposed approach for recording sequences of ground-level spherical panoramic images. The proposed approach has two advantages. First, detected camera trajectories are more accurate and stable (compared to methods using multi-view planar images only) due to the use of spherical panoramic images. Second, we extract the texture of a facade of a building from a single panoramic image. Thus, there is no need to deal with color blending problems that typically occur when using overlapping textures.

• Journal of information and communication convergence engineering
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• v.11 no.4
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• pp.298-306
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• 2013

The scale invariant feature transform (SIFT) is an effective algorithm used in object recognition, panorama stitching, and image matching. However, due to its complexity, real-time processing is difficult to achieve with current software approaches. The increasing availability of parallel computers makes parallelizing these tasks an attractive approach. This paper proposes a novel parallel approach for SIFT algorithm implementation using a block filtering technique in a Gaussian convolution process on the SIMD Pixel Processor. This implementation fully exposes the available parallelism of the SIFT algorithm process and exploits the processing and input/output capabilities of the processor, which results in a system that can perform real-time image and video compression. We apply this implementation to images and measure the effectiveness of such an approach. Experimental simulation results indicate that the proposed method is capable of real-time applications, and the result of our parallel approach is outstanding in terms of the processing performance.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.39-52
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• 2009

Scale Invariant Feature Transform (SIFT) is an effective algorithm in object recognition, panorama stitching, and image matching, however, due to its complexity, real time processing is difficult to achieve with software approaches. This paper proposes using a reconfigurable hardware processor with integer half kernel. The integer half kernel Gaussian reduces the Gaussian pyramid complexity in about half [] and the reconfigurable processor carries out a parallel implementation of a full search Fast SIFT algorithm. We use a low memory, fine grain single instruction stream multiple data stream (SIMD) pixel processor that is currently being developed. This implementation fully exposes the available parallelism of the SIFT algorithm process and exploits the processing and I/O capabilities of the processor which results in a system that can perform real time image and video compression. We apply this novel implementation to images and measure the effectiveness. Experimental simulation results indicate that the proposed implementation is capable of real time applications.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.06a
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• pp.229-230
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• 2019

실사 기반의 VR (Virtual Reality) 영상을 생성하기 위해서는 카메라 리그 (rig) 설계 기술, 스티칭(stitching) 기술, 3 차원 공간 정보 추정 기술 등 여러 기술이 필요하다. 이러한 기술에 대한 연구를 진행하려면 카메라 위치, 피사체 거리, 조명 정도 등 다양한 요소를 고려한 수 많은 실험을 수행해야 하는데, 실사 조건에서 이를 직접 수행하려면 상당한 시간과 노력이 소요된다. 따라서 원하는 실험 조건을 쉽게 구성할 수 있는 컴퓨터 그래픽스 (CG: Computer Graphics) 환경 상에서 먼저 실험을 진행한 이후 실사로 확장하는 것이 더욱 효율적인 접근법이 될 것이다. 본 논문에서는 VR 영상의 생성에 요구되는 다양한 기술을 연구할 때 활용할 수 있는 CG 기반의 툴을 소개하고자 한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.11a
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• pp.131-132
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• 2018

비디오 스티칭은 카메라 간 변환 관계인 호모그래피를 이용하여 스티칭하는 것이 일반적이다. 본 논문은 호모그래피를 이용한 고정형 비디오 스티칭에서 조도 변화, 노이즈 등으로 일관되지 않는 특징점 추출과 유니폼한 입력 영상으로 적은 특징점이 추출되는 경우에 대하여 정확도 높은 호모그래피 추출이 가능한 특징점 누적 기반 고정형 비디오 스티칭 방법을 제안한다. 실험을 통해 단일 프레임 특징점을 이용한 결과 영상에 비해 특징점 누적을 이용하는 경우 영상 내 부정합 영역 등의 왜곡이 크게 감소하였음을 확인하였다.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.499-505
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• 2022

Recently, the metaverse has been receiving a lot of attention. Metaverse means a virtual space, and various events can be held in this space. In particular, 360-degree video, a format optimized for the metaverse space, is attracting attention. A 360-degree video image is created by stitching images taken with multiple cameras or lenses in all 360-degree directions. When shooting a 360-degree video, a variety of shooting equipment, including a shooting staff to take a picture of a subject in front of the camera, is displayed on the video. Therefore, when shooting a 360-degree video, you have to hide everything except the subject around the camera. There are several problems with this shooting method. Among them, lighting is the biggest problem. This is because it is very difficult to install a fixture that focuses on the subject from behind the camera as in conventional image shooting. This study is an experimental study to find the optimal angle for 360-degree images by adjusting the angle of indoor lighting. We propose a method to record 360-degree video without installing additional lighting. Based on the results of this study, it is expected that experiments will be conducted through more various shooting angles in the future, and furthermore, it is expected that it will be helpful when using 360-degree images in the metaverse space.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.85-92
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• 2019

In this paper, we propose a efficient feature point extraction method that can solve the problem of performance degradation by introducing a preprocessing process when extracting feature points by utilizing the characteristics of 360-degree realistic media. 360-degree realistic media is composed of images produced by two or more cameras and this image combining process is accomplished by extracting feature points at the edges of each image and combining them into one image if they cover the same area. In this production process, however, the stitching process where images are combined into one piece can lead to the distortion of non-seamlessness. Since the realistic media of 4K-class image has higher resolution than that of a general image, the feature point extraction and matching process takes much more time than general media cases.

• Journal of IKEEE
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• v.24 no.2
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• pp.529-535
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• 2020

As the main technology of the 4th industrial revolution, immersive 360-degree video contents are drawing attention. The market size of immersive 360-degree video contents worldwide is projected to increase from $6.7 billion in 2018 to approximately $70 billion in 2020. However, most of the immersive 360-degree video contents are distributed through illegal distribution networks such as Webhard and Torrent, and the damage caused by illegal reproduction is increasing. Existing 2D video industry uses copyright filtering technology to prevent such illegal distribution. The technical difficulties dealing with immersive 360-degree videos arise in that they require ultra-high quality pictures and have the characteristics containing images captured by two or more cameras merged in one image, which results in the creation of distortion regions. There are also technical limitations such as an increase in the amount of feature point data due to the ultra-high definition and the processing speed requirement. These consideration makes it difficult to use the same 2D filtering technology for 360-degree videos. To solve this problem, this paper suggests a feature point extraction and identification technique that select object identification areas excluding regions with severe distortion, recognize objects using deep learning technology in the identification areas, extract feature points using the identified object information. Compared with the previously proposed method of extracting feature points using stitching area for immersive contents, the proposed technique shows excellent performance gain.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.6
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• pp.831-838
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• 2011

Computer vision research area, a division of computer graphics application area that creates realistic visualization in computer, conducts vigorously researches on developing realistic 3D model or virtual environment. As the popularization and development of 3D display makes common users easy to experience a solid 3D virtual reality, the demand for virtual reality contents are increasing. This paper proposes 3D panorama system using depth point location-based depth map generation method. 3D panorama using depth map gives an effect that makes users feel staying at real place and looking around nearby circumstances. Also, 3D panorama gives free sight point for both nearby object and remote one and provides solid 3D video.

• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.3-24
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• 2019

Techniques related to 360 VR service have been developed to improve the quality of the stitched image and video, where illumination compensation scheme is one of the important tools. Among the conventional illumination compensation algorithms, Gain-based compensation and Block Gain-based compensation algorithms have shown the outstanding performances in the process of making panorama picture. However, those are ineffective in the 360 VR service, because the disparity between illuminations of the multiple pictures in 360 VR is much more than that in making the panorama picture. In addition, the number of the pictures to be stitched in 360 VR system is more than that in the conventional panorama image system. Thus, we propose a preprocessing tool to enhance the illumination compensation algorithm so that the method reduces the degradation in the stitched picture of 360 VR systems. The proposed algorithm consists of 'color compensation' and 'illumination compensation'. The simulation results show that the proposed technique improve the conventional techniques without additional complexity.