• Title/Summary/Keyword: 포인트클라우드 데이터

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Extraction and Utilization of DEM based on UAV Photogrammetry for Flood Trace Investigation and Flood Prediction (침수흔적조사를 위한 UAV 사진측량 기반 DEM의 추출 및 활용)

  • Jung-Sik PARK;Yong-Jin CHOI;Jin-Duk LEE
    • Journal of the Korean Association of Geographic Information Studies
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    • v.26 no.4
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    • pp.237-250
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    • 2023
  • Orthophotos and DEMs were generated by UAV-based aerial photogrammetry and an attempt was made to apply them to detailed investigations for the production of flood traces. The cultivated area located in Goa-eup, Gumi, where the embankment collapsed and inundated inundation occurred due to the impact of 6th Typhoon Sanba in 2012, was selected as rhe target area. To obtain optimal accuracy of UAV photogrammetry performance, the UAV images were taken under the optimal placement of 19 GCPs and then point cloud, DEM, and orthoimages were generated through image processing using Pix4Dmapper software. After applying CloudCompare's CSF Filtering to separate the point cloud into ground elements and non-ground elements, a finally corrected DEM was created using only non-ground elements in GRASS GIS software. The flood level and flood depth data extracted from the final generated DEM were compared and presented with the flood level and flood depth data from existing data as of 2012 provided through the public data portal site of the Korea Land and Geospatial Informatix Corporation(LX).

Stereoscopic Video Compositing with a DSLR and Depth Information by Kinect (키넥트 깊이 정보와 DSLR을 이용한 스테레오스코픽 비디오 합성)

  • Kwon, Soon-Chul;Kang, Won-Young;Jeong, Yeong-Hu;Lee, Seung-Hyun
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38C no.10
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    • pp.920-927
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    • 2013
  • Chroma key technique which composes images by separating an object from its background in specific color has restrictions on color and space. Especially, unlike general chroma key technique, image composition for stereo 3D display requires natural image composition method in 3D space. The thesis attempted to compose images in 3D space using depth keying method which uses high resolution depth information. High resolution depth map was obtained through camera calibration between the DSLR and Kinect sensor. 3D mesh model was created by the high resolution depth information and mapped with RGB color value. Object was converted into point cloud type in 3D space after separating it from its background according to depth information. The image in which 3D virtual background and object are composed obtained and played stereo 3D images using a virtual camera.

Massive 3D Point Cloud Visualization by Generating Artificial Center Points from Multi-Resolution Cube Grid Structure (다단계 정육면체 격자 기반의 가상점 생성을 통한 대용량 3D point cloud 가시화)

  • Yang, Seung-Chan;Han, Soo Hee;Heo, Joon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.30 no.4
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    • pp.335-342
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    • 2012
  • 3D point cloud is widely used in Architecture, Civil Engineering, Medical, Computer Graphics, and many other fields. Due to the improvement of 3D laser scanner, a massive 3D point cloud whose gigantic file size is bigger than computer's memory requires efficient preprocessing and visualization. We suggest a data structure to solve the problem; a 3D point cloud is gradually subdivided by arbitrary-sized cube grids structure and corresponding point cloud subsets generated by the center of each grid cell are achieved while preprocessing. A massive 3D point cloud file is tested through two algorithms: QSplat and ours. Our algorithm, grid-based, showed slower speed in preprocessing but performed faster rendering speed comparing to QSplat. Also our algorithm is further designed to editing or segmentation using the original coordinates of 3D point cloud.

Robust Estimation of Hand Poses Based on Learning (학습을 이용한 손 자세의 강인한 추정)

  • Kim, Sul-Ho;Jang, Seok-Woo;Kim, Gye-Young
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.12
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    • pp.1528-1534
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    • 2019
  • Recently, due to the popularization of 3D depth cameras, new researches and opportunities have been made in research conducted on RGB images, but estimation of human hand pose is still classified as one of the difficult topics. In this paper, we propose a robust estimation method of human hand pose from various input 3D depth images using a learning algorithm. The proposed approach first generates a skeleton-based hand model and then aligns the generated hand model with three-dimensional point cloud data. Then, using a random forest-based learning algorithm, the hand pose is strongly estimated from the aligned hand model. Experimental results in this paper show that the proposed hierarchical approach makes robust and fast estimation of human hand posture from input depth images captured in various indoor and outdoor environments.

Performance Evaluation of Denoising Algorithms for the 3D Construction Digital Map (건설현장 적용을 위한 디지털맵 노이즈 제거 알고리즘 성능평가)

  • Park, Su-Yeul;Kim, Seok
    • Journal of KIBIM
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    • v.10 no.4
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    • pp.32-39
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    • 2020
  • In recent years, the construction industry is getting bigger and more complex, so it is becoming difficult to acquire point cloud data for construction equipments and workers. Point cloud data is measured using a drone and MMS(Mobile Mapping System), and the collected point cloud data is used to create a 3D digital map. In particular, the construction site is located at outdoors and there are many irregular terrains, making it difficult to collect point cloud data. For these reasons, adopting a noise reduction algorithm suitable for the characteristics of the construction industry can affect the improvement of the analysis accuracy of digital maps. This is related to various environments and variables of the construction site. Therefore, this study reviewed and analyzed the existing research and techniques on the noise reduction algorithm. And based on the results of literature review, performance evaluation of major noise reduction algorithms was conducted for digital maps of construction sites. As a result of the performance evaluation in this study, the voxel grid algorithm showed relatively less execution time than the statistical outlier removal algorithm. In addition, analysis results in slope, space, and earth walls of the construction site digital map showed that the voxel grid algorithm was relatively superior to the statistical outlier removal algorithm and that the noise removal performance of voxel grid algorithm was superior and the object preservation ability was also superior. In the future, based on the results reviewed through the performance evaluation of the noise reduction algorithm of this study, we will develop a noise reduction algorithm for 3D point cloud data that reflects the characteristics of the construction site.

Visible Height Based Occlusion Area Detection in True Orthophoto Generation (엄밀 정사영상 제작을 위한 가시고도 기반의 폐색영역 탐지)

  • Youn, Junhee;Kim, Gi Hong
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.3D
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    • pp.417-422
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    • 2008
  • With standard orthorectification algorithms, one can produce unacceptable structure duplication in the orthophoto due to the double projection. Because of the abrupt height differences, such structure duplication is a frequently occurred phenomenon in the dense urban area which includes multi-history buildings. Therefore, occlusion area detection especially for the urban area is a critical issue in generation of true orthophoto. This paper deals with occlusion area detection with visible height based approach from aerial imagery and LiDAR. In order to accomplish this, a grid format DSM is produced from the point clouds of LiDAR. Next, visible height based algorithm is proposed to detect the occlusion area for each camera exposure station with DSM. Finally, generation of true orthophoto is presented with DSM and previously produced occlusion maps. The proposed algorithms are applied in the Purdue campus, Indiana, USA.

Development of PCD and Parametric Based Retaining wall BIM Models for Maintenance (유지관리용 PCD 및 파라메트릭 기반 옹벽 BIM 모델 생성 기술 개발)

  • Su-Been Ma;Min-Jin Lee;Da-Hyeon Yang;Hyun-Jin Jung;Jong-Han Lee
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.28 no.6
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    • pp.88-94
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    • 2024
  • This study introduces a technique for generating parametric BIM models of retaining walls using point cloud data (PCD). Efficient maintenance requires reflecting the current representation of retaining walls, accounting for any discrepancies between the as-built structure and initial drawing. For this, a RANSAC-based algorithm was employed to extract the height and path coordinates from acquired and refined PCD. BIM models were then automatically generated by defining sectional parameters. Applied to a real retaining wall, the algorithm demonstrated a maximum height extraction error of 1.77% and a path coordinate extraction error of 0.88%. This method offers a way to automatically generate BIM models, even when basic data is limited, and there is a the potential to enhance the efficiency of retaining wall maintenance.

Development of Multi-Camera based Mobile Mapping System for HD Map Production (정밀지도 구축을 위한 다중카메라기반 모바일매핑시스템 개발)

  • Hong, Ju Seok;Shin, Jin Soo;Shin, Dae Man
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.39 no.6
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    • pp.587-598
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    • 2021
  • This study aims to develop a multi-camera based MMS (Mobile Mapping System) technology for building a HD (High Definition) map for autonomous driving and for quick update. To replace expensive lidar sensors and reduce long processing times, we intend to develop a low-cost and efficient MMS by applying multiple cameras and real-time data pre-processing. To this end, multi-camera storage technology development, multi-camera time synchronization technology development, and MMS prototype development were performed. We developed a storage module for real-time JPG compression of high-speed images acquired from multiple cameras, and developed an event signal and GNSS (Global Navigation Satellite System) time server-based synchronization method to record the exposure time multiple images taken in real time. And based on the requirements of each sector, MMS was designed and prototypes were produced. Finally, to verify the performance of the manufactured multi-camera-based MMS, data were acquired from an actual 1,000 km road and quantitative evaluation was performed. As a result of the evaluation, the time synchronization performance was less than 1/1000 second, and the position accuracy of the point cloud obtained through SFM (Structure from Motion) image processing was around 5 cm. Through the evaluation results, it was found that the multi-camera based MMS technology developed in this study showed the performance that satisfies the criteria for building a HD map.

Development of Remote Measurement Method for Reinforcement Information in Construction Field Using 360 Degrees Camera (360도 카메라 기반 건설현장 철근 배근 정보 원격 계측 기법 개발)

  • Lee, Myung-Hun;Woo, Ukyong;Choi, Hajin;Kang, Su-min;Choi, Kyoung-Kyu
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.26 no.6
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    • pp.157-166
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    • 2022
  • Structural supervision on the construction site has been performed based on visual inspection, which is highly labor-intensive and subjective. In this study, the remote technique was developed to improve the efficiency of the measurements on rebar spacing using a 360° camera and reconstructed 3D models. The proposed method was verified by measuring the spacings in reinforced concrete structure, where the twelve locations in the construction site (265 m2) were scanned within 20 seconds per location and a total of 15 minutes was taken. SLAM, consisting of SIFT, RANSAC, and General framework graph optimization algorithms, produces RGB-based 3D and 3D point cloud models, respectively. The minimum resolution of the 3D point cloud was 0.1mm while that of the RGB-based 3D model was 10 mm. Based on the results from both 3D models, the measurement error was from 10.8% to 0.3% in the 3D point cloud and from 28.4% to 3.1% in the RGB-based 3D model. The results demonstrate that the proposed method has great potential for remote structural supervision with respect to its accuracy and objectivity.

A Study on Construction & Management of Urban Spatial Information Based on Digital Twin (디지털트윈 기반의 도시 공간정보 구축 및 관리에 관한 연구)

  • Lih, BongJoo
    • Journal of Cadastre & Land InformatiX
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    • v.53 no.1
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    • pp.47-63
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    • 2023
  • The Seoul Metropolitan Government is building and operating digital twin-based urban spatial information to solve various problems in the city and provide public services. Two essential factors to ensure the stable utilization of spatial information for the implementation of such a digital twin city are the latest and quality of the data. However, it is time-consuming and costly to maintain continuous updating of high-quality urban spatial information. To overcome this problem, we studied efficient urban spatial information construction technology and the operation, management, and update procedures of construction data. First, we demonstrated and applied automatic 3D building construction technology centered on point clouds using the latest hybrid sensors, confirmed that it is possible to automatically construct high-quality building models using high-density airborne lidar results, and established an efficient data management plan. By applying differentiated production methods by region, supporting detection of urban change areas through Seoul spatial feature identifiers, and producing international standard data by level, we strengthened the utilization of urban spatial information. We believe that this study can serve as a good precedent for local governments and related organizations that are considering activating urban spatial information based on digital twins, and we expect that discussions on the construction and management of spatial information as infrastructure information for city-level digital twin implementation will continue.