• 한국측량학회지
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• 제31권4호
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• pp.331-339
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• 2013

LiDAR 측량은 고밀도로 정확하게 거리를 측정하는 장점 때문에 지표면과 지표면 위의 객체를 3D 모델링하는데 사용되는 주요기술 중의 하나이다. 본 연구의 목적은 고밀도 LiDAR 데이터와 RANSAC 알고리즘을 이용하여 자동으로 철도전력선을 탐지하고 모델링하는 방법을 개발하는데 있다. 철도전력선을 탐지하기 위하여 레이저 데이터의 다중반사 특성과 철도전력선에 대한 형상정보를 이용한다. 이를 위한 프로세스는 최초 단위라인을 찾기 위한 직육면체 분석과 라인 추적, 연결 그리고 색인 작업으로 구성되며, 반복 RANSAC과 라인 파라미터를 구하기 위한 최소제곱법이 모델링을 위하여 사용된다. 철도전력선의 경우에는 정확도 확인을 위한 실측자료를 구하는 것이 매우 힘들어서 정량적인 정확도 평가가 어려우나 모델에 대한 레이저점군의 표준편차는 x-y 및 z 좌표 각각 8cm와 5cm로 양호하였고, 육안 검사에 의한 완성도면에서도 원 데이터와 비교할 때 모든 철도전력선 라인이 탐지 및 모델링된 것을 알 수 있었다. 본 연구에서 제시하는 방법의 모든 과정은 완전히 자동화하였으며, 특히 다수의 전력선이 복잡하게 설치된 지역에서도 적용될 수 있도록 개발하였다.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2009년도 춘계 종합학술대회 논문집
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• pp.485-487
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• 2009

원격탐사 LiDAR 영상 Data를 중심으로 하는 정사보정하고 기존의 이미 취득한 2차원적인 평면사진을 지상기준점에 의하여 정밀기하보정을 하여 얻은 사진영상자료를 이용하여 3차원 공간정보로 구성하기 위해서는 동일지역에 대한 수준 측량결과인 높이 데이터를 매칭 하였다. 즉 항공기에 탑재한 LiDAR 의하여 모든 대상지에 대한 지형지물의 고밀도의 높이 값을 획득하여 위치보정 작업 후에 3-D로 매칭할 수는 방법을 연구하여 실험하도록 하였다. 이것은 지형도가 제공할 수 없는 지형도의 평균높이를 산출하여 3차원의 공간지형을 다양한 시점에서 투영시킬 수 있어 조감도 뿐 아니라 필요한 측정치를 산출할 수 있도록 하였다. 이번 연구에서는 항공사진의 지형의 표고 값을 레이져 데이터와의 중첩기법을 이용하여 원하는 계획노선에 대한 투시도 및 토공량 산정 등의 단면을 도형화하여 비교하여 국토 지형공간정보 수집 및 편집에서 다양한 활용이 가능하도록 하였다. 그 결과, 원격탐사 LiDAR 영상 Data를 중심으로 하는 정사보정하고 이에 매칭 할 수 있는 수치지도 벡터와의 통합 및 전환으로 U-city에서의 3차원 공간에서 지형모델의 생성과 다양한 활용을 제시하였다.

• 한국농공학회논문집
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• 제66권3호
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• pp.1-14
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• 2024

Gaining an accurate 3D stream geometry has become feasible with Unmanned Aerial Vehicle (UAV), which is crucial for better understanding stream hydrodynamic processes. The objective of this study was to investigate series of filters to remove stream vegetation and propose the best method for generating Digital Terrain Models (DTMs) using UAV-based point clouds. A stream reach approximately 500 m of the Bokha stream in Icheon city was selected as the study area. Point clouds were obtained in August 1st, 2023, using Phantom 4 multispectral and Zenmuse L1 for Structure from Motion (SfM) and Light Detection And Ranging (LiDAR) respectively. Three vegetation filters, two morphological filters, and six composite filters which combined vegetation and morphological filters were applied in this study. The Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were used to assess each filters comparing with the two cross-sections measured by leveling survey. The vegetation filters performed better in SfM, especially for short vegetation areas, while the morphological filters demonstrated superior performance on LiDAR, particularly for taller vegetation areas. Overall, the composite filters combining advantages of two types of filters performed better than single filter application. The best method was the combination of Progressive TIN (PTIN) and Color Indicies of Vegetation Extraction (CIVE) for SfM, showing the smallest MAE of 0.169 m. The proposed method in this study can be utilized for constructing DTMs of stream and thus contribute to improving the accuracy of stream hydrodynamic simulations.

• 대한토목학회논문집
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• 제28권3D호
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• pp.417-422
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• 2008

전통적인 정사영상 제작기법으로는 이중 투영으로 인한 원치 않는 구조물의 중복이 정사영상 안에 생길 수 있다. 특히 고층 빌딩이 밀집된 도심지역에서는 고도의 변화가 심하여 이러한 현상이 자주 발생한다. 이러한 문제들로 인하여 도심지역의 폐색영역 탐지는 정확한 엄밀 정사영상(true orthophoto)의 제작에 있어서 매우 중요한 문제이다. 본 논문은 항공영상과 LiDAR로부터 가시고도 기반의 폐색영역 탐지기법을 다루고 있다. 본 논문에서는 LiDAR의 포인트 클라우드 데이터로부터 격자형태의 수치표고모형(DSM)을 제작한 후, DSM과 항공영상의 촬영점을 이용한 가시고도 기반의 폐색영역 탐지기법을 제안하였다. 마지막으로 만들어진 DSM과 전 과정에서 만들어진 폐색맵을 이용한 엄밀 정사영상의 제작과정을 기술하였다. 제안된 알고리즘은 미국 인디애나 주의 퍼듀 캠퍼스 지역에 적용되었다.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2010년 춘계학술발표회 논문집
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• pp.285-287
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• 2010

It is recently enlarged to necessity of 3D spatial information model in urban areas. and in order to that, It is increased to use the terrestrial LiDAR. The Point clouds which are received by terrestrial LiDAR take a relateive coordinate. For transform into absolute coordinate, it carry out GPS surveying. However, it is difficult to geo-referencing of point clouds using the GPS due to high buildings and facilities in urban area. This study suggests a methodology, that is geo-referencing of point clouds which is received from terresstrial LiDAR in urban area and then verified accuracy of geo-referencing of point clouds. In order to geo-Referencing of point clouds which are received in Engineering building of Yonsei Univ., it was be setout through GPS surveying, and then obtained absolute coordinate of real building. Using this coordinate, It was operated geo-referencing of point clouds, verified accuracy between check point and geo-referenced point clouds. As a result, RMSE of check point shows that GPS surveying is 6.9~8.0cm.

• 한국측량학회지
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• 제38권5호
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• pp.425-433
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• 2020

Three-dimensional data has been used for different applications such as robotics, building reconstruction, and so on. 3D data can be generated from an optical camera or a laser scanner. Especially, a wearable multi-sensor system including the above-mentioned sensors is an optimized structure that can overcome the drawbacks of each sensor. After finding the geometric relationships between sensors, georeferencing of the datasets acquired from the moving system, should be carried out. Especially, in an indoor environment, error propagation always causes problem in the georeferencing process. To improve the accuracy of this process, other sources of data were used to combine with LiDAR (Light Detection and Ranging) data, and various registration methods were also tested to find the most suitable way. More specifically, this paper proposed a new process of NDT (Normal Distribution Transform) to register the LiDAR point cloud, with additional information from other sensors. For real experiment, a wearable mapping system was used to acquire datasets in an indoor environment. The results showed that applying the new process of NDT and combining LiDAR data with IMU (Inertial Measurement Unit) information achieved the best result with the RMSE 0.063 m.

• ETRI Journal
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• 제45권5호
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• pp.847-861
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• 2023

Dynamic object detection is essential for ensuring safe and reliable autonomous driving. Recently, light detection and ranging (LiDAR)-based object detection has been introduced and shown excellent performance on various benchmarks. Although LiDAR sensors have excellent accuracy in estimating distance, they lack texture or color information and have a lower resolution than conventional cameras. In addition, performance degradation occurs when a LiDAR-based object detection model is applied to different driving environments or when sensors from different LiDAR manufacturers are utilized owing to the domain gap phenomenon. To address these issues, a sensor-fusion-based object detection and classification method is proposed. The proposed method operates in real time, making it suitable for integration into autonomous vehicles. It performs well on our custom dataset and on publicly available datasets, demonstrating its effectiveness in real-world road environments. In addition, we will make available a novel three-dimensional moving object detection dataset called ETRI 3D MOD.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2007년도 춘계학술발표회 논문집
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• pp.93-96
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• 2007

LIDAR is a relatively new technological tool that can be used to accurately georeference terrain features, and also is becoming an important 3D mapping tool in GIS. In this study it is described the capabilities of terrestrial LIDAR that was used to build a 3D terrain model of extremely steep rock face, along with the useful data and examples of contributions terrestrial lidar has made to outcrop studies. For this, High-resolution terrestrial lidar acquisition, processing, interpretation are discussed and applied to mapping of geological surfaces in three dimensions. We expected that lidar is a tool with which we can improve our current field methods and quantify the observations geologists make.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2007년도 춘계학술발표회 논문집
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• pp.121-125
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• 2007

Recently, constructing and complementing the road network database are a main key in all social operation in our life. However it needs high expenses for constructing and complementing the data, and relies on many people for finishing the tasks. This study propose a novel method to extract urban road networks from 3-D LiDAR data automatically. This method integrates height, reflectance, and clustered road point information. Geometric information of general roads is also applied to cluster road points group correctly. The proposed method has been tested on various urban areas which contain complicated road networks. The results conclude that the integration of height, reflectance, and geometric information worked reliably to cluster road points.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.633-636
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• 2004

Airborne laser scanning thechnology has been studied in many applications, DSM(Digital Surface Model) development, building extraction, 3D virtual city modeling. In this paper, we will evaluate the possibility of airborne laser scanning technology for transportation application, especially for recognizing moving vehicles on road. First, we initially segment the region of roads from all LiDAR DATA using the GIS map and intensity image. Secondly, the segmented region is divided into the roads and vehicles using the height threshold value of local based window. Finally, the vehicles will be classified into the several types of vehicles by MDC(Minimum Distance Classification) method using the vehicle's geometry information, height, length, width, etc