Journal of the Korea Academia-Industrial cooperation Society (한국산학기술학회논문지)

The Korea Academia-Industrial cooperation Society (한국산학기술학회)
권호 표지
DOI QR코드

DOI QR Code

Visualization of Structural Shape Information based on Octree using Terrestrial Laser Scanning

3D레이저스캐닝을 이용한 옥트리기반 구조물 형상정보 가시화

  • Cha, Gichun (Department of Convergence Engineering for Future City, Sungkyunkwan University) ;
  • Lee, Donghwan (Department of Convergence Engineering for Future City, Sungkyunkwan University) ;
  • Park, Seunghee (School of Civil, Architectural Engineering and Landscape Architecture, Sungkyunkwan University)
  • 차기춘 (성균관대학교 미래도시융합공학과) ;
  • 이동환 (성균관대학교 미래도시융합공학과) ;
  • 박승희 (성균관대학교 건설환경공학부)
  • Received : 2016.06.01
  • Accepted : 2016.08.11
  • Published : 2016.08.31
Download PDF
⟨ Previous Next ⟩

Abstract

This study presents the visualization of shape information based on Octree using 3D laser scanning. The process of visualization was established to construct the Octree structure from the 3D scan data. The scan data was converted to a 2D surface through the mesh technique and the surface was then converted to a 3D object through the Raster/Vector transformation. The 3D object was transmitted to the Octree Root Node and The shape information was constructed by the recursive partitioning of the Octree Root Node. The test-bed was selected as the steel bridge structure in Sungkyunkwan University. The shape information based on Octree was condensed into 89.3%. In addition, the Octree compressibility was confirmed to compare the shape information of the office building, a computer science campus in Germany and a New College in USA. The basis is created by the visualization of shape information for double-deck tunnel and it will be expected to improve the efficiency of structural health monitoring and maintenance.

본 논문은 대형구조물의 형상관리를 위해 3D 레이저 스캐닝을 이용하여 옥트리기반 구조물 형상정보 가시화를 진행하였다. 이를 위해 3D스캔데이터를 옥트리 데이터 구조로 변환할 수 있는 프로세스를 정립하고, 메쉬기법과 래스터/백터변환 처리를 통해 점(point) 데이터가 2차원 면 형태를 거처 3D객체로 생성되는 프로세스를 진행하였다. 생성된 3D객체는 옥트리 데이터 구조로 전달할 수 있는 형식인 Binary file type로 변환하는 작업이 진행되었고, 변환된 Binary file을 옥트리 최상의 노드인 Root노드로 전달하였다. Root 노드를 시작으로 옥트리 내부에서의 세부분할 작업 후 내부노드 데이터 저장과 비어있는 영역제거를 통해 옥트리기반 구조물 형상정보모델을 구축하였다. 본 연구가 수행된 Test-bed는 성균관대학교 내에 위치한 강교량 구조물로, 구축된 옥트리기반 형상정보는 스캔데이터를 89.3% 압축하였으며 독일의 사무용빌딩, 대학캠퍼스와 미국 소재 단과대학건물 스캔데이터와의 비교를 통하여 옥트리 데이터 압축률을 확인하였다. 본 연구를 통해 대형구조물 및 복층터널의 내부형상정보관리를 위한 형상정보 가시화의 기반을 마련하였으며, 형상정보 가시화를 통해 구조물 모니터링 및 유지관리 효율을 높일 수 있을 것이라 기대한다.

Keywords

References

  1. Lee, H. M., "Improved Model for Measurement of Displacements and Deformed Shapes of Beam Structures using Terrestrial Laser Scanning" JOURNAL OF THE ARCHITECTURAL INSTITUTE OF KOREA Structure & Construction, Vol. 24, No. 4, pp. 3-14, 2008.
  2. Bae, S. W., "A Terrestrial LiDAR Based Method for Detecting Structural Deterioration, and Its Application to Tunnel Maintenance", The Journal of Engineering Geology, Vol. 25, No. 2, pp. 227-235, 2015. DOI: http://dx.doi.org/10.9720/kseg.2015.2.227
  3. Yang, S. C., Han, S. H., Heo, J., "Massive 3D Point Cloud Visualization by Generating Artificial Center Points from Multi-Resolution Cube Grid Structure", Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 30, No. 4, pp. 335-342, 2012. DOI: http://dx.doi.org/10.7848/ksgpc.2012.30.4.335
  4. Delaunay, "Sur la sphere vide", Izvestia Akademii Nauk SSSR, Otdelenie Matematicheskikh i Estestvennykh Nauk, Vol. 7, pp. 793-800, 1934.
  5. Gustav K., "Uber die Reduktion der positiven quadratischen Formen mit drei unbestimmten ganzen Zahlen", Journal fur die Reine und Angewandte Mathematik, Vol. 40, pp. 209-227, 1850.
  6. Westover L., "Interactive Volume Rendering", Proceedings of the 1989 Chapel Hill workshop on Volume visualization, ACM, New York, pp. 9-18, 1989. DOI: http://dx.doi.org/10.1145/329129.329138
  7. Rusinkiewicz S., trimesh2, Princeton University, New Jersey, http://gfx.cs.princeton.edu/proj/trimesh2 (last date accessed: 13 Apr. 2016).
  8. Dachsbacher C., Vogelgsang C. and Stamminger M., "Sequential Point Trees", ACM Transactions on Graphics, ACM, Vol. 22, No. 3, pp. 657-662, 2003. DOI: http://dx.doi.org/10.1145/882262.882321
  9. Han, S. H., "Implementation of File-referring Octree for Huge 3D Point Clouds", Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 32, No. 2, pp. 109-115, 2014. DOI: http://dx.doi.org/10.7848/ksgpc.2014.32.2.109
  10. Gobbetti E. and Marton F., "Layered Point Clouds: a simple and efficient multiresolution structure for distributing and rendering gigantic point-sampled models", Computers & Graphics, Pergamon Press, Vol. 28, No. 6, pp. 815-826, 2004. DOI: http://dx.doi.org/10.1016/j.cag.2004.08.010
  11. Pajarola R., Sainz M. and Lario R., "XSplat: External Memory Multiresolution Point Visualization", International Conference on Visualization, Imaging and Image Processing, IEEE Computer Society, Benidorm, pp. 628-633, 2005.
  12. Wimmer M. and Scheiblauer C., "Instant Points : Fast Rendering of Unprocessed Point Clouds", Proceedings Symposium on Point-Based Graphics 2006, Eurographics Association, Boston, pp. 129-136, 2006.
  13. Wand M et al., "Interactive Editing of Large Point Clouds", Proceedings of Symposium on Point-Based Graphics 2007, Eurographics Association, Prague, pp. 37-46, 2007.
  14. Goswami P et al., "High Quality Interactive Rendering of Massive Point Models using Multi-way kd-Trees", Proceedings of the 18th Pacific Conference on Computer Graphics and Applications 2010, IEEE Computer Society, pp. 93-100, 2010. DOI: http://dx.doi.org/10.1109/PacificGraphics.2010.20
  15. Saxena, M., Finnigan, P. M., Graichen, C. M., Hathaway, A.F., and Parthasarathy, V. N., "Octree-based automatic mesh generation for non-manifold domains", Engineering with Computers, Vol. 11, pp. 1-14, 1995. DOI: http://dx.doi.org/10.1007/BF01230440
  16. Woo, H. ,Kang, E., Wang, S., and Lee, K. H., "A new segmentation method for point cloud data", International Journal of Machine Tools and Manufacture, Vol. 42, pp. 167-178, 2002. DOI: http://dx.doi.org/10.1016/S0890-6955(01)00120-1
  17. Wang, M. and Tseng, Y.-H., "Lidar data segmentation and classification based on octree structure", XXth ISPRS Congress, ISPRS, Istanbul, Turkey, 2004.
  18. Schnabel, R., Wahl, R., and Klein, R., "Efficient RANSAC for point-cloud shape detection", Computer Graphics Forum, Vol. 26, pp. 214-226, 2007. DOI: http://dx.doi.org/10.1111/j.1467-8659.2007.01016.x
  19. Cho, H., Cho, W., Park, J., and Song, N., "3D building modeling using aerial LiDAR data", Korean Journal of Remote Sensing, Vol. 24, pp. 141-152, 2008. https://doi.org/10.7780/kjrs.2008.24.2.141
  20. Marechal, L., "Advances in octree-based allhexahedral mesh generation: handling sharp features", 18th International Meshing Roundtable, Salt Lake City, UT, USA, pp. 65-84, 2009.
  21. Han, S., Lee, S., Kim, S. P., Kim, C., Heo, J., and Lee, H., "A Comparison of 3D R-tree and octree to index large point clouds from a 3D terrestrial laser scanner", Korean Journal of Geomatics, Vol. 29, No. 1, pp. 531-537, 2011. DOI: http://dx.doi.org/10.7848/ksgpc.2011.29.1.39
  22. Han, S., Kim, S., Jung, J. H., Kim, C., Yu, K., and Heo, J., "Development of a hashing-based data structure for the fast retrieval of 3D terrestrial laser scanned data", Computers & Geosciences, Vol. 39, pp. 1-10, 2012. DOI: http://dx.doi.org/10.1016/j.cageo.2011.05.005
  23. Kim, Y. J., Kim, J. J., "Compression of Normal Vectors using Octree Encoding", Society of CAD/CAM Engineers, Vol.12, No.4 pp. 109-117, 2007.
  24. Ryu, J. H., "Efficient Octree Encoding for Real Time Transmission of 3D Geometry Data Through Internet", Society of CAD/CAM Engineers, Vol. 7, No. 4, pp. 262-268, 2002.
  25. CloudCompare, "Octree Structure", 2015[cited 2015 Feb 20], Available From: http://www.cloudcompare.org/. (accessed Mar., 16, 2016)
  26. Elseberg, J., Borrmann D., "One billion points in the cloud - an octree for efficient processing of 3D laser scans", International Society for Photogrammetry and Remote Sensing, Vol. 76, pp. 76-88, 2013. DOI: http://dx.doi.org/10.1016/j.isprsjprs.2012.10.004
  27. Elseberg, J., Borrmann D., "Efficient Processing of Large 3D Point Clouds", Information, Communication and Automation Technologies (ICAT), 2011 XXIII International Symposium, pp. 1-7, Oct, 2011. DOI: http://dx.doi.org/10.1145/800031.808576
  28. Tamminen, M., "Efficient Octree Conversion by Connectivity Labeling", Proceedings of the 11th Annual Conference on Computer Graphics and Interactive Techniques, 1984.
  29. Autonomy Intelligent Systeme, Albert-Ludwigs-Universitat Freiburg, Available From: http://ais.informatik.uni-freiburg.de/projects/datasets/octomap/ (accessed 26 Apr, 2016)