• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.5
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• pp.33-41
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• 2011

In this paper, we propose a lossless compression scheme for cloud point data of the target construction by using doubleness and decreasing useless information of cloud point data. We use Hough transform to find the horizontal angle between construction and terrestrial LIDAR. This angle is used for the rotation of the cloud point data. The cloud point data can be parallel to x-axis, then y-axis doubleness is increased. Therefore, the cloud point data can be more compressed. In addition, we apply two methods to decrease the number of cloud point data for useless information of them. One is decimation of the cloud point data, the other is to extract the range of y-coordinates of target construction, and then extract the cloud point data existing in the range only. The experimental result shows the performance of proposed scheme. To compress the data, we use only the position information without additional information. Therefore, this scheme can increase processing speed of the compression algorithm.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.493-498
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• 2006

본 논문에서는 3D 파노라믹 가상 환경 생성을 위한 투영기반 메쉬 모델 생성 기법을 제안한다. 제안된 메쉬 모델 생성 기법은 멀티뷰 카메라를 이용해 다수의 시점에서 얻은 실내 환경의 3D 데이터로부터 메쉬 모델을 생성한다. 먼저 미리 보정된 카메라 파라미터를 이용해 입력된 임의의 3D점 데이터를 여러 개의 하위 점군으로 분할한다. 적응적 샘플링을 통해 각 하위 점군으로부터 중복되는 점 데이터를 없애고 새로운 점군을 생성한다. 각각의 하위 점군을 Delaunay삼각화 방법을 통해 메쉬 모델링하고, 인접한 하위 점군의 메쉬들을 통합하여 하나의 메쉬 모델을 생성한다. 제안된 메쉬 모델링 방법은 점군의 분할을 통해 각 부분의 메쉬 모델을 독립적으로 생성하므로 실내 환경과 같은 넓은 영역의 모델링에 알맞다. 또한, 적응적 샘플링을 통해 3D 데이터가 갖는 깊이 정보의 특징을 보존하면서 메쉬 데이터의 크기를 줄인다. 생성된 가상 환경 모델은 가상/증강현실 응용 어플리케이션 등에 적용이 가능하다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.1
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• pp.35-41
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• 2020

3D laser scanners are an effective way to quickly acquire a large amount of data about an object. Recently, it is used in various fields such as surveying, displacement measurement, 3D data generation of objects, construction of indoor spatial information, and BIM(Building Information Model). In order to utilize the point cloud data acquired through the 3D laser scanner, it is necessary to make the data acquired from many stations through a matching process into one data with a unified coordinate system. However, analytical researches on the accuracy of point cloud data according to the registration method are insufficient. In this study, we tried to analyze the accuracy of registration method of point cloud data acquired through 3D laser scanner. The point cloud data of the study area was acquired by 3D laser scanner, the point cloud data was registered by the ICP(Iterative Closest Point) method and the shape registration method through the data processing, and the accuracy was analyzed by comparing with the total station survey results. As a result of the accuracy evaluation, the ICP and the shape registration method showed 0.002m~0.005m and 0.002m~0.009m difference with the total station performance, respectively, and each registration method showed a deviation of less than 0.01m. Each registration method showed less than 0.01m of variation in the experimental results, which satisfies the 1: 1,000 digital accuracy and it is suggested that the registration of point cloud data using ICP and shape matching can be utilized for constructing spatial information. In the future, matching of point cloud data by shape registration method will contribute to productivity improvement by reducing target installation in the process of building spatial information using 3D laser scanner.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.143-151
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• 2009

In this paper, a new extraction algorithm for artificial structure in 3D cloud points of terrestrial LIDAR is described, considering that various obstacles in terrestrial LIDAR make it difficult to apply conventional algorithms which are designed for air-born LIDAR data. Firstly we use the R, G, B color information from the terrestrial LIDAR data to discriminate among the massive 3D cloud points. Hough transform is then applied to estimate the straight lines that correspond to the target structure. Finally, the structure is extracted by comparing the distance between the estimated line and 3D cloud points. The proposed algorithm is efficient in the sense that it requires the user interaction only when the reference colors are obtained. Computer simulation shows the performance to be quite satisfactory.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.421-422
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• 2020

발 고유 변인 측정 및 데이터의 수집은 소비자의 발 건강을 위한 신발 제작을 위하여 필요하다. 신발의 설계 지표 또한 개정의 필요성이 제시되고 있어 발 고유 변인 측정의 및 데이터 획득에 관한 연구의 필요성이 증대되고 있다. 본 논문에서는 발 형태의 데이터 값을 산출하여 사용자에게 적합한 맞춤형 인솔 및 신발을 제작하고, 신발의 설계 지표를 산출하기 위하여 발 고유 변인의 데이터 값을 자동으로 측정이 가능한 발 고유 변인 산출이 가능한 발 형상 추출 시스템에 대해 서술한다. 이를 위해 사용자의 발 고유 변인 측정을위한 스캐닝 스테이지를 설계 및 제작하고, 3대의 깊이 카메라를 설치하였다. 잡음 및 배경을 제거하기 위해 가우시안 배경 모델링으로 전경 영역을 분리하여 발 점군 데이터를 획득 한 후, Euclidean transformation을 통해 각 점군 데이터를 정합한다. 실험 결과에서는 획득된 발 형상 점군 데이터와 접지면 형상 및 발 변인 추출 결과를 보여준다.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.141-142
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• 2008

본 논문은 텍스처된 3차원 점군데이터를 효율적으로 모델링하는 방법을 제안한다. 지상라이다로부터 획득한 3차원 점군데이터는 많은 노이즈를 가지고 있으며 이로 인해 자동적인 모델링이 어렵다. 3차원 모델링에 있어서 메쉬를 생성해야 3차원 랜더링이 가능하지만 3차원 메쉬 생성은 노이즈에 취약하기 때문에 디자이너들이 수작업으로 노이즈를 제거해야만 한다. 하지만 노이즈 자제가 지상 라이다로부터 들어온 데이터이기 때문에 자동적인 노이즈 제거가 어렵다. 본 논문에서는 텍스처된 지상 라이다 데이터로부터 칼라 영상의 정보를 이용한 윤곽선 정보 검출 방법을 제안한다. 대부분의 건물과 같은 구조물에서 최 외곽은 같은 색의 정보를 가지고 있다. 최 외곽 칼라의 정보를 이용하여 칼라 정보의 변화를 제한하고, 유사 칼라 정보를 가지고 있는 픽셀만 얻어냄으로써 최외각 정보를 얻어낸다. 칼라 이미지를 이용만 필터링 된 점군데이터는 xy, xz, yz 각각의 평면에서 윤곽선 데이터를 가지며 이는 구조물에 대한 모델링의 속도를 빠르게 해준다.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.12
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• pp.77-86
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• 2015

It is difficult to extract small valve automatically in noisy 3D point cloud obtained from LIDAR because small object is affected by noise considerably. In this paper, we assume that the valve is a complex model consisting of torus, cylinder and plane represents handle, rib and center plane to extract a pose of the valve. And to extract the pose, we received additional input: center of the valve. We generated histogram of distance between the center and each points of point cloud, and obtain pose of valve by extracting parameters of handle, rib and center plane. Finally, the valve is reconstructed.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.99-110
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• 2023

In this paper, we propose a system termed ForestLi that can accurately estimate the diameter at breast height (DBH) and tree height using LiDAR point cloud data. The ForestLi system processes LiDAR point cloud data through the following steps: downsampling, outlier removal, ground segmentation, ground height normalization, stem extraction, individual tree segmentation, and DBH and tree height measurement. A commercial system, such as LiDAR360, for processing LiDAR point cloud data requires the user to directly correct errors in lower vegetation and individual tree segmentation. In contrast, the ForestLi system can automatically remove LiDAR point cloud data that correspond to lower vegetation in order to improve the accuracy of estimating DBH and tree height. This enables the ForestLi system to reduce the total processing time as well as enhance the accuracy of accuracy of measuring DBH and tree height compared to the LiDAR360 system. We performed an empirical study to confirm that the ForestLi system outperforms the LiDAR360 system in terms of the total processing time and accuracy of measuring DBH and tree height.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.495-507
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• 2023

The roughness of discontinuity significantly influences the mechanical characteristics of rock masses and extensively affects thermal and hydraulic behaviors. In this study, we utilized photogrammetry to generate 3D point cloud data for discontinuity and applied this data to characterize the roughness of discontinuity. The discontinuity profiles, reconstructed from the 3D point cloud data, were compared with those manually measured using a profile gauge. This comparison served to validate the accuracy and reliability of the acquired point cloud data in replicating the actual configurations of rock surfaces. Subsequent to this validation, influence of the number of profiles for representative JRC assessment was further investigated followed by suggestion of roughness anisotropy evaluation method with application of it to actual rock discontinuity surfaces.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.10
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• pp.2443-2450
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• 2014

In the motion recognition system using depth image, the depth image is converted to the real world formed 3D point cloud data for efficient algorithm apply. And then, output depth image is converted by the projective world after algorithm apply. However, when coordinate conversion, rounding error and data loss by applied algorithm are occurred. In this paper, when convert 3D point cloud data to depth image, we proposed efficient conversion method and its hardware implementation without rounding error and data loss according image size change. The proposed system make progress using the OpenCV and the window program, and we test a system using the Kinect in real time. In addition, designed using Verilog-HDL and verified through the Zynq-7000 FPGA Board of Xilinx.