• Title/Summary/Keyword: Cloud point

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Using Drone and Laser Scanners for As-built Building Information Model Creation of a Cultural Heritage Building (드론 및 레이저스캐너를 활용한 근대 건축물 문화재 빌딩정보 모델 역설계 구축에 관한 연구)

  • Jung, Rae-Kyu;Koo, Bon-Sang;Yu, Young-Su
    • Journal of KIBIM
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    • v.9 no.2
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    • pp.11-20
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    • 2019
  • The use of drones and laser scanners have the potential to drastically reduce the time and costs of conventional techniques employed for field survey of cultural heritage buildings. Moreover, point cloud data can be utilized to create an as-built Building Information Model (BIM), providing a repository for consistent operations information. However, BIM creation is not a requisite for heritage buildings, and their technological possibilities and barriers have not been documented. This research explored the processes required to convert a heritage university building to a BIM model, using existing off-the-shelf software applications. Point cloud data was gathered from drones for the exterior, while a laser scanner was employed for the interior of the building. The point clouds were preprocessed and used as references for the geometry of the building elements, including walls, slabs, windows, doors, and staircases. The BIM model was subsequently created for the individual elements using existing and custom libraries. The model was used to extract 2D CAD drawings that met the requirements of Korea's heritage preservation specifications. The experiment showed that technical improvements were needed to overcome issues of occlusion, modeling errors due to modeler's subjective judgements and point cloud data cleaning and filtering techniques.

A study on the 2D floor plan derivation of the indoor Point Cloud based on pixelation (포인트 클라우드 데이터의 픽셀화 기반 건축물 실내의 2D도면 도출에 관한 연구)

  • Jung, Yong-Il;Oh, Sang-Min;Ryu, Min-Woo;Kang, Nam-Woo;Cho, Hun-hee
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2020.06a
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    • pp.105-106
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    • 2020
  • Recently, a method of deriving an efficient 2D floor plan has been attracting attention for remodeling of old buildings with inaccurate 2D floor plans, and thus, studies on reverse engineering of indoor Point Cloud Date(PCD) have been actively conducted. However, in the case of a indoor PCD, due to interference of indoor objects, available equipment is limited to Mobile Laser Scanner(MLS), which causes a efficiency reduction of data processing. Therefore, this study proposes an automatic derivation algorithm for 2D floor plan of indoor PCD based on pixelation. First, the scanned indoor PCD is projected on the XY coordinate plane. Second, a point distribution of each pixel in the projected PCD is derived using a pixelation. Lastly, 2 floor plan derivation based on the algorithm is performed.

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Three Dimensional Metrology of Surface Mounted Solder Pastes Using Bounding Box Formed by Histogram of Gradient Vectors of Point Cloud (점군의 기울기벡터 히스토그램에 의해 형성된 구속상자를 이용한 표면실장 솔더페이스트의 3차원 Metrology)

  • 신동원
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2003.06a
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    • pp.674-677
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    • 2003
  • This work presents a method of point-to-surface assignment for 3D inspection of solder pastes on PCB. A bounding box enclosing the solder paste tightly on all sides is introduced to avoid incorrect point-to-surface assignment. The shape of bounding box for solder paste brick is variable according to geometry of measured points. The surface geometry of the bounding box is obtained by using five peaks selected from the histogram of normalized gradient vectors for measured points. By using the bounding box enclosing the solder paste. the task of point-to-surface assignment is successfully executed. Subsequently, the geometrical features are obtained via surface fitting.

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Projection Loss for Point Cloud Augmentation (점운증강을 위한 프로젝션 손실)

  • Wu, Chenmou;Lee, Hyo-Jone
    • Proceedings of the Korea Information Processing Society Conference
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    • 2019.05a
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    • pp.482-484
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    • 2019
  • Learning and analyzing 3D point clouds with deep networks is challenging due to the limited and irregularity of the data. In this paper, we present a data-driven point cloud augmentation technique. The key idea is to learn multilevel features per point and to reconstruct to a similar point set. Our network is applied to a projection loss function that encourages the predicted points to remain on the geometric shapes with a particular target. We conduct various experiments using ShapeNet part data to evaluate our method and demonstrate its possibility. Results show that our generated points have a similar shape and are located closer to the object.

Novel ICP Matching to Efficiently Interpolate Augmented Positions of Objects in AR (AR에서 객체의 증강 위치를 효율적으로 보간하기 위한 새로운 ICP 매칭)

  • Moon, YeRin;Kim, Jong-Hyun
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2022.07a
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    • pp.563-566
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    • 2022
  • 본 논문에서는 증강현실에서 객체 증강 시, 특징점과 GPS를 이용하여 증강 위치를 효율적으로 보간할 수 있는 ICP(Iterative closest point) 매칭 기법을 제안한다. 다양한 환경에서 제한받지 않고 객체를 증강하기 위해 일반적으로 마커리스(Markerless) 방식을 사용하며, 대표적으로 평면 검출과 페이스 검출을 사용한다. 이는 현실과 자연스러운 동기화를 위한 것으로 계산은 작지만, 인식의 범위가 넓기 때문에 증강 위치에 대한 오차가 존재한다. 이러한 작은 오차는 특정 산업에서는 치명적일 수 있으며, 특히 건설이나 의료시설에서 발생하면 큰 사고로 이어진다. 객체를 증강 시킬 때 해당 환경에 대한 점 구름(Point cloud)을 수집하여 데이터베이스에 저장한다. 본 논문에서는 관측되는 점 구름과의 오차를 줄이기 위해 ICP 매칭 기법을 사용하며, 실린더 기반의 각도 보간을 이용하여 계산량을 줄인다. 결과적으로 특징점과 GPS를 이용하여 ICP 매칭 기법을 통해 효율적으로 처리함으로써, 증강 위치에 대한 정확도가 개선된 증강 방식을 보여준다.

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A study on the extraction of boundary points of point group segmented from LIDAR point cloud (LIDAR 포인트 cloud에서 분리된 포인트 군집의 윤곽 포인트 추출에 관한 연구)

  • Han, Soo-Hee;Lee, Jeong-Ho;Yu, Ki-Yun;Kim, Yong-Il
    • Proceedings of the KSRS Conference
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    • 2007.03a
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    • pp.148-152
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    • 2007
  • 본 연구에서는 LIDAR 포인트 자료로부터 분리된 포인트 군집의 윤곽 포인트 추출을 위하여,가상격자를 이용한 검색 영역의 제한을 통한 윤곽 포인트 추출 방식을 제안하였으며 성능을 평가하기 위해 보편적으로 사용되는 TIN을 이용한 방식과 비교하였다. 실제 건물 포인트 자료에 대하여 적용한 결과 TIN을 이용한 방식보다 빠른 처리가 가능하며 시각적인 평가를 통해 결과물의 품질 면에서도 두 가지 방식이 거의 유사함을 확인할 수 있었다.

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Depth-based Mesh Modeling for Virtual Environment Generation (가상 환경 생성을 위한 깊이 기반 메쉬 모델링)

  • 이원우;우운택
    • Proceedings of the IEEK Conference
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    • 2003.11b
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    • pp.111-114
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    • 2003
  • In this paper, we propose a depth-based mesh modeling method to generate virtual environment. The proposed algorithm constructs mesh model from unorganized point cloud obtained from a multi-view camera. We separate the point cloud consisting objects from the background. Then, we apply triangulation to each object and background. Since the objects and the background are modeled independently, it is possible to construct effective virtual environment. The application of proposed modeling method is applicable to entertainment, such as movie and video game and effective virtual environment generation.

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Dense Neural Network Graph-based Point Cloud classification (밀집한 신경망 그래프 기반점운의 분류)

  • El Khazari, Ahmed;lee, Hyo Jong
    • Proceedings of the Korea Information Processing Society Conference
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    • 2019.05a
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    • pp.498-500
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    • 2019
  • Point cloud is a flexible set of points that can provide a scalable geometric representation which can be applied in different computer graphic task. We propose a method based on EdgeConv and densely connected layers to aggregate the features for better classification. Our proposed approach shows significant performance improvement compared to the state-of-the-art deep neural network-based approaches.

An Assessment of the Effectiveness of Cloud Seeding as a Measure of Air Quality Improvement in the Seoul Metropolitan Area (서울에서의 미세먼지 저감을 위한 인공강수 가능성 진단)

  • Song, Jae In;Yum, Seong Soo
    • Atmosphere
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    • v.29 no.5
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    • pp.609-614
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    • 2019
  • Cloud seeding experiment has been proposed as a way to alleviate severe air pollution problem because, if successful, artificially produced precipitation through cloud seeding could scavenge out some portion of air pollutants. As a first step to verify the practicality of such experiment, seedability of the clouds observed in Seoul is assessed by examining statistical characteristics of some relevant meteorological variables. Analyses of 9 years of Korea Meteorological Agency Seoul station data indicate that as PM10 mass concentration increases, cloud amount, liquid water path, and ice water path decrease, but the difference between temperature and dew point temperature tends to increase. Such finding suggests that cloud seeding becomes less feasible as air pollution becomes more severe in the Seoul metropolitan area, at least in a statistical sense. For some individual severe air pollution events, however, seedable clouds may exist and indeed cloud seeding experiments can be successful. Therefore, detailed investigation on cloud seedability for individual severe air pollution events are highly required to make a concrete assessment of cloud seeding as a way to alleviate severe air pollution problem.

What makes University Students to continuously use Cloud Services? - Enjoyment and Social Influence

  • Lee, Jong Man;Lee, Sang Jong
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.1
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    • pp.123-129
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    • 2018
  • The purpose of this paper is to investigate the influence of utilitarian, hedonic and social motivations on continuance intention to use cloud services. To do this, this study built a research model and examined how ease of use, usefulness, enjoyment, social influence affect the continuance usage intention of cloud services. The survey method was used for this paper, and data from a total of 82 university students were used for the analysis. And structural equation model was used to analyze the data. The results of this empirical study is summarized as followings. First, enjoyment has a direct effect on the continuance usage intention of cloud services. Second, social influence has a direct effect on the continuance usage intention. Further, it will provide meaning suggestion point of the importance of not only utilitarian motivation but also hedonic and social motivations in establishing the use policy of cloud services.