한국측량학회지 (Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography)

  • 제38권1호
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  • Pages.35-41
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  • 2020
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  • 1598-4850(pISSN)
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  • 2288-260X(eISSN)
한국측량학회 (Korean Society of Surveying, Geodesy, Photogrammetry and Cartography)
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점군데이터 정합 방법에 따른 정확도 평가

Accuracy Evaluation by Point Cloud Data Registration Method

  • Park, Joon Kyu (Department of Civil Engineering, Seoil University) ;
  • Um, Dae Yong (Civil Engineering, Korea National University of Transportation)
  • 투고 : 2020.02.13
  • 심사 : 2020.02.25
  • 발행 : 2020.02.29
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초록

3D 레이저 스캐너는 대상물에 대한 많은 양의 데이터를 빠른 시간 내에 취득할 수 있는 효과적인 방법으로 최근 측량, 변위측정, 대상물의 3차원 데이터 생성, 실내공간정보 구축, BIM (Building Information Model) 등 다양한 분야에 활용되고 있다. 3D 레이저 스캐너를 통해 취득되는 점군데이터의 활용을 위해서는 정합과정을 거쳐 많은 측점에서 취득한 데이터를 통일된 좌표체계를 가진 하나의 데이터로 만드는 과정이 필요하다. 따라서 정합 방법에 따른 점군데이터의 정확도에 대한 분석적 연구가 필요하다 이에 본 연구에서는 3D 레이저 스캐너를 통해 취득되는 점군데이터의 정합방법에 따른 정확도를 분석하고자 하였다. 3D 레이저 스캐너를 통해 연구대상지의 점군데이터를 취득하고, 자료처리를 통해 ICP (Iterative Closest Point) 와 형상정합 방법에 의해 점군데이터를 정합하였으며, 토털스테이션 측량성과와 비교하여 정확도를 분석하였다. 정확도 평가 결과 ICP와 형상정합 방법은 각각 토털스테이션 성과와 0.002~0.005m, 0.002~0.009m의 차이를 나타내었다. 각각의 정합 방법은 실험결과 모두 0.01m 미만의 편차를 나타내어 1:1,000 수치지형도의 허용정확도를 만족하였으며, ICP 및 형상정합을 이용한 점군데이터의 정합이 공간정보 구축에 충분히 활용 가능함을 제시하였다. 향후 형상정합 방법에 의한 점군데이터의 정합은 3D 레이저 스캐너를 활용한 공간정보 구축 과정에서 타겟의 설치를 줄임으로써 생산성 향상에 기여할 것이다.

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.

키워드

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피인용 문헌

  1. 3D 레이저스캐너를 활용한 유류 저장탱크의 검사 vol.21, pp.12, 2020, https://doi.org/10.5762/kais.2020.21.12.867
  2. 건설현장 3차원 점군 데이터 정합 정확성 향상을 위한 중첩비율 분석 vol.11, pp.4, 2021, https://doi.org/10.13161/kibim.2021.11.4.001