• 한국컴퓨터정보학회논문지
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• 제25권5호
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• pp.81-90
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• 2020

직접 측정방법을 기반으로 3차원 스캔 데이터에서 유방의 자동측정을 위한 유방과 관련된 측정점 설정과 이상적인 3차원 스캔 자세를 제안하였다. 특히 직접 측정법에서의 유방 바깥쪽점은 체형과 자세에 따라 변동되기 쉬우므로 3차원 측정법에서는 유방에서 찾는 새로운 방법을 제안하였다. 유방의 윤곽선이 뚜렷하지 않은 유방 위쪽의 유방 위쪽점은 겨드랑접힘점을 기준으로 설정되는데 직접측정법에서의 유방 위쪽점이 3차원 스캔데이터에서 측정된 유방위쪽점보다 높게 설정됨을 알 수 있었다. 그러므로 직접 측정치와 3차원 측정치 간의 오차를 줄이기 위해서는 유방 위쪽점 설정에 관여되는 겨드랑앞접힘점 위치가 명확해야 할 것이다. 유방과 관련된 깊이 항목에서는 유방 바깥쪽점을 제외한 모든 깊이에서 직접 측정치가 높게 나타났는데 이는 피부 눌림에 의한 것으로 판단된다. 또 유방의 굴곡이 심한 유방아래길이와 유방아래 접힘선길이, 유방 안쪽점사이 간격은 굴곡에 의해 3차원 측정치가 직접 측정치보다 높게 나타나 유방에 대한 3차원 측정법이 일반화되기 위해서는 다양한 유방유형에 따른 측정치의 변화를 연구할 필요가 있다.

• Journal of Information Display
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• 제10권1호
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• pp.6-15
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• 2009

In this paper, a new approach is proposed for the efficient generation of computer-generated holograms (CGHs) using the spatially redundant data on a 3D object and the novel look-up table (N-LUT) method. First, the pre-calculated N-point principle fringe patterns (PFPs) were calculated using the 1-point PFP of the N-LUT. Second, spatially redundant data on a 3D object were extracted and re-grouped into the N-point redundancy map using the run-length encoding (RLE) method. Then CGH patterns were generated using the spatial redundancy map and the N-LUT method. Finally, the generated hologram patterns were reconstructed. In this approach, the object points that were involved in the calculation of the CGH patterns were dramatically reduced, due to which the computational speed was increased. Some experiments with a test 3D object were carried out and the results were compared with those of conventional methods.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제3권8호
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• pp.251-260
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• 2014

3D 점 데이터는 높은 정확성을 가진 사물의 표면 정보 데이터로 다양한 분야에서 사용되고 있으며, 특히 지리학에서 지형 파악과 분석에 많이 사용되고 있다. 일반적으로 3D 점 데이터의 Gridding 과정을 거치게 되는데 이는 불연속적인 점 데이터를 일정한 좌표 값으로 만드는 과정으로 긴 실행 시간과 높은 비용이 필요하다. 특히 Gridding 과정 중 보간 작업을 위해서 Kriging이 높은 정확성으로 주목받고 있지만 처리과정이 복잡하고 연산이 많아 처리속도가 상대적으로 느리기 때문에 많이 사용되지 않고 있다. 본 논문에서는 Gridding을 고성능으로 처리하기위해 Kriging 연산 과정을 병렬화했으며 격자 자료구조를 MapReduce 패러다임에 맞게 변형하여 Kriging에 적용하였다. 실험은 항공 LiDAR 데이터 약 1.6백만 개와 4.3백만 개의 점 데이터를 이용해서 제안한 MapReduce 구조에 적용하였고, 그 결과 3대의 이기종 클러스터에서 전체 실행시간이 순차적 프로그램에 비해 최대 3.4배 단축하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권6호
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• pp.3108-3120
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• 2019

Point cloud is widely used in 3D applications due to the recent advancement of 3D data acquisition technology. Polygonal mesh-based compression has been dominant since it can replace many points sharing a surface with a set of vertices with mesh structure. Recent point cloud-based applications demand more point-based interactivity, which makes point cloud compression (PCC) becomes more attractive than 3D mesh compression. Interestingly, an exploration activity has been started to explore the feasibility of PCC standard in MPEG. In this paper, a new color attribute compression method is presented for point cloud data. The proposed method utilizes the spatial redundancy among color attribute data to construct a color palette. The color palette is constructed by using K-means clustering method and each color data in point cloud is represented by the index of its similar color in palette. To further improve the compression efficiency, the spatial redundancy between the indices of neighboring colors is also removed by marking them using a flag bit. Experimental results show that the proposed method achieves a better improvement of RD performance compared with that of the MPEG PCC reference software.

• 한국멀티미디어학회논문지
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• 제24권11호
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• pp.1518-1525
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• 2021

Due to the growth of VR industry and rise of digital twin industry, the importance of implementing 3D data same as real space is increasing. However, the fact that it requires expertise personnel and huge amount of time is a problem. In this paper, we propose a system that generates point cloud data with same shape and color as a real space, just by scanning the space. The proposed system integrates 3D geometric information from lidar and color information from stereo camera into one point cloud. Since the number of 3D points generated by lidar is not enough to express a real space with good quality, some of the pixels of 2D image generated by camera are mapped to the correct 3D coordinate to increase the number of points. Additionally, to minimize the capacity, overlapping points are filtered out so that only one point exists in the same 3D coordinates. Finally, 6DoF pose information generated from lidar point cloud is replaced with the one generated from camera image to position the points to a more accurate place. Experimental results show that the proposed system easily and quickly generates point clouds very similar to the scanned space.

• 대한조선학회논문집
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• 제59권4호
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• pp.235-242
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• 2022

As ship condition inspection technology has been developed, research on collecting, analyzing, and diagnosing condition information has become active. In ships, related research has been conducted, such as analyzing, detecting, and classifying major hull failures such as cracks and corrosion using 2D and 3D data information. However, for geometric deformation such as indents and bulges, 2D data has limitations in detection, so 3D data is needed to utilize spatial feature information. In this study, we aim to detect hull structural deformation positions. It builds a specimen based on actual hull structure deformation and acquires a point cloud from a model scanned with a 3D scanner. In the obtained point cloud, deformation(outliers) is found with a combination of RANSAC algorithms that find the best matching model in the Octree data structure and dataset.

• 한국정밀공학회지
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• 제32권7호
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• pp.633-641
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• 2015

In this study, we proposed a three-dimensional (3D) scanning system based on laser-vision technique and rotary mechanism for automatic 3D model reconstruction. The proposed scanning system consists of a laser projector, a camera, and a turntable. For laser-camera calibration a new and simple method was proposed. 3D point cloud data of the surface of scanned object was fully collected by integrating extracted laser profiles, which were extracted from laser stripe images, corresponding to rotary angles of the rotary mechanism. The obscured laser profile problem was also solved by adding an addition camera at another viewpoint. From collected 3D point cloud data, the 3D model of the scanned object was reconstructed based on facet-representation. The reconstructed 3D models showed effectiveness and the applicability of the proposed 3D scanning system to 3D model-based applications.

• 한국정보통신학회논문지
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• 제25권10호
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• pp.1452-1455
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• 2021

Recently, point clouds are generated by capturing real space in 3D, and it is actively applied and serviced for performances, exhibitions, education, and training. These point cloud data require post-correction work to be used in virtual environments due to errors caused by the capture environment with sensors and cameras. In this paper, we propose an enhancement technique for 3D point cloud data by applying generative adversarial network(GAN). Thus, we performed an approach to regenerate point clouds as an input of GAN. Through our method presented in this paper, point clouds with a lot of noise is configured in the same shape as the real object and environment, enabling precise interaction with the reconstructed content.

• 한국산업융합학회 논문집
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• 제25권3호
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• pp.397-406
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• 2022

Recently, research and development to revitalize smart construction are being actively carried out. Accordingly, 3D mapping technology that digitizes construction site is drawing attention. To create a 3D digital map for construction site a point cloud generation method based on LiDAR(Light detection and ranging) using MMS(Mobile mapping system) is mainly used. The purpose of this study is to analyze the accuracy of MMS LiDAR-based point cloud data. As a result, accuracy of MMS point cloud data was analyzed as dx = 0.048m, dy = 0.018m, dz = 0.045m on average. In future studies, accuracy comparison of point cloud data produced via UAV(Unmanned aerial vegicle) photogrammetry and MMS LiDAR should be studied.

• 한국측량학회지
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• 제40권1호
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• pp.1-14
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• 2022

굴착 현장에서 신속·정확·안전한 측량을 위해 본 연구에서는 드론을 이용한 지하 시설물 측량의 적용 가능성 및 3D 시각화의 기대효과를 다음과 같이 도출하였다. Phantom4 Pro 20MP의 드론으로 30m의 비행 고도, 중복도 85%의 비행계획으로 0.85mm의 GSD (Ground Sampling Distance)값을 확보하였고, GCP (Groud Control Point)4점과 검사점 2점을 계산하여 기준점에 대하여 7.3mm, 검사점은 11mm의 성과를 취득할 수 있었다. 저가의 드론으로 측량할 경우 GCP의 중요성이 확인되었으며, 지상 기준점이 없는 경우, X값의 오차 범위는 -81.2cm에서 +90.0cm, Y값의 오차 범위는 +6.8cm에서 155.9 cm 값을 도출하였다. Pix4D 프로그램을 이용하여 포인트 클라우드 데이터를 분류하였다. 지하 시설물 데이터와 도로 포장면의 데이터를 분류하고, 중첩과정을 통해 실제 모형의 도로와 지하 시설물의 데이터를 3D 시각화하였다. 중첩된 포인트 클라우드 데이터는 Open Source 프로그램인 CloudCompare를 통해 사용자가 원하는 장소의 위치와 심도 정보를 확인할 수 있게 되었다. 본 연구결과로 지하 시설물 측량의 새로운 패러다임으로 자리매김하게 될 것이다.