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Extraction and Modeling of Curved Building Boundaries from Airborne Lidar Data

항공라이다 데이터의 건물 곡선경계 추출 및 모델링

  • Lee, Jeong Ho (Engineering Research Institute, Seoul National University) ;
  • Kim, Yong Il (Dept. of Construction and Environmental Eng., Seoul National University)
  • 이정호 (서울대학교 공학연구소) ;
  • 김용일 (서울대학교 건설환경공학부)
  • Received : 2012.11.14
  • Accepted : 2012.12.13
  • Published : 2012.12.30

Abstract

Although many studies have been conducted to extract buildings from airborne lidar data, most of them assume that all the boundaries of a building are straight line segments. This makes it difficult to model building boundaries containing curved segments correctly. This paper aims to model buildings containing curved segments as combination of straight lines and arcs. First, two sets of boundary points are extracted by adaptive convex hull algorithm and local convex hull algorithm with a larger radius. Then, arc segments are determined by average spacing of boundary points and intersection ratio of perpendicular lines. Finally, building boundary is modeled through regularization of least squares line or circle fitting. The experimental results showed that the proposed method can model the curved building boundaries as arc segments correctly by completeness of 69% and correctness of 100%. The approach will be utilized effectively to create automatically digital map that meets the conditions of the Korean digital mapping.

항공라이다 데이터를 이용한 건물 추출 연구가 많이 진행되어 오고 있으나 대부분의 연구는 건물경계를 직선으로 가정하기 때문에 곡선경계가 포함된 건물의 경계를 올바르게 모델링하지 못하는 한계가 있다. 본 논문은 곡선경계를 포함하는 건물을 항공라이다 데이터로부터 직선과 곡선이 혼합된 경계로 모델링하는 것을 목적으로 한다. 건물점들에 대하여 적응적 컨벡스헐 알고리즘과 큰 반경의 국지적 컨벡스헐 알고리즘을 적용하여 두 세트의 경계점을 추출한다. 경계점들의 평균 점 간격 및 수직이등분선의 교차 비율에 의하여 곡선 세그먼트를 판별한 후, 직선과 곡선 세그먼트에 대하여 각각 다른 정규화 방법을 적용하여 건물경계를 모델링한다. 실험결과, 곡선 세그먼트의 추출 완전성과 정확성이 각각 69%, 100%로서 본 연구의 방법을 통해 대부분의 곡선경계를 올바르게 추출 및 모델링 할 수 있었다. 본 연구의 결과는 수치지도 제작기준을 만족하는 건물경계를 자동으로 생성하는데 효과적으로 활용될 수 있을 것이다.

Keywords

References

  1. Alharthy, A. and J. Bethel, 2002, Heuristic filtering and 3d feature extraction from LiDAR data, PCV02, ISPRS Commission III Symposium 2002, ISPRS, September9-13, Graz, Austria.
  2. Cho. W. S, Jwa, Y. S., and Lee, Y. J., 2003, Automatic extraction of buildings from airborne laser scanning data, Journal of the Korean Society of Civil Engineers, Korean Society of Civil Engineers, No. 23, Vol. 5, pp. 591-751.
  3. Choi, S. P., Cho, J. H., and Kim, J. S., 2011, An filtering automatic technique of LiDAR data by multiple linear regression analysis, Journal of the Korean Society for GeoSpatial Information System, KOGSIS, No. 19, Vol. 4, pp. 109-118.
  4. Dorninger, P. and N. Pfeifer, 2008, A comprehensive automated 3d approach for building extraction, reconstruction, and regularization from airborne laser scanning point clouds, Sensors, MDPI AG, Vol. 8, pp. 7323-7343.
  5. Edelsbrunner, H., D. Kirkpatrick, and R. Seidel, 1983, On the shapes of a set of points in the plane, IEEE Transactions on Information Theory, IEEE, IT29(4), pp. 551-559.
  6. Fu, C.S., and J. Shan, 2004, 3-D building reconstruction from unstructured distinct points, International Archives of Photogrammetry and Remote Sensing, ISPRS, Vol. 35, Part B3, unpaginated.
  7. Habib, A. F., R. Zhai, and C. Kim, 2010, Generation of complex polyhedral building models by integrating stereo-aerial imagery and lidar data, Photogrammetric Engineering and Remote Sensing, ASPRS, Vol. 76, No. 5, pp. 609-623. https://doi.org/10.14358/PERS.76.5.609
  8. Jarvis, R. A., 1997, Computing the shape hull of points in the plane, Proceedings of IEEE Computer Society Conference Pattern Recognition and Image Processing, IEEE, pp. 231-241.
  9. Jung, H. S., Lim, S. B., and Lee, D. C., 2008, Utilizing airborne LiDAR data for building extraction and superstructure analysis for modeling, Korean Journal of Geomatics, KSGPC, No. 26, Vol. 3, pp. 227-239.
  10. Kim, E. M., 2009, Building boundary extraction of airborne LIDAR data by image-based and pointbased data analysis, Journal of the Korean Society for GeoSpatial Information System, KOGSIS, No. 17, Vol. 1, pp. 119-129.
  11. Kim, H. T., 2001, Fusion of lidar data and photogrammetric imagery for autonomous generation of building layers in GIS, Ph. D. Dissertation, Seoul National University.
  12. Kim, S. J., and Lee, I. P., 2010, Simulation based performance assessment of a LIDAR data segmentation algorithm, Journal of the Korean Society for GeoSpatial Information System, KOGSIS, No. 18, Vol. 2, pp. 119-129.
  13. Lach, S. and J. Kerekes, 2008, Robust extraction of exterior building boundaries from topographic lidar Data, IEEE Proc. IGARSS, IEEE, Boston, USA, pp. 85-88.
  14. Lee, D. H., 2008, Fusion of DSM and photogrammetric imagery for reliable building extraction, Ph. D. Dissertation, Seoul National University.
  15. Lee, J. H., and Lee. D. C., 2010, LiDAR data segmentation using aerial images for building modeling, Korean Journal of Geomatics, KSGPC, No. 28, Vol. 1, pp. 47-56.
  16. Lee, J. H., Yeom, J. H., and Kim, Y. I., 2011, Filtering airborne laser scanning data by utilizing adjacency based on scan line, Korean Journal of Geomatics, KSGPC, No. 29, Vol. 4, pp. 221-227. https://doi.org/10.7848/ksgpc.2011.29.4.359
  17. Lee, J. H., and Kim, Y. I., 2012, Building boundary reconstruction from airborne lidar data by adaptive convex hull algorithm, Korean Journal of Geomatics, KSGPC, No. 30, Vol. 3, pp. 305-312. https://doi.org/10.4218/etrij.11.1610.0022
  18. Lee, J., S. Han, Y. Byun, and Y. Kim, 2011, Extraction and regularization of various building boundaries with complex shapes utilizing distribution characteristics of airborne LIDAR points, ETRI Journal, ETRI, Vol. 33, No. 4, pp. 547-557. https://doi.org/10.4218/etrij.11.1610.0022
  19. Ma, R., 2004, Building model reconstruction from lidar data and aerial photographs, Dissertation, The Ohio State University.
  20. Oh, J. H., 2001, A study on the extraction of building boundary from laser scanning data, Master's Thesis, Seoul National University.
  21. Sampath, A., and J. Shan, 2007, Building boundary tracing and regularization from airborne lidar point clouds, PE&RS, ASPRS, Vol. 73, No. 7, pp. 805-812.
  22. Shan, J. and A. Sampath, 2005, Urban DEM generation from raw LIDAR data: a labeling algorithm and its performance, PE&RS, ASPRS, Vol. 71, No. 2, 2005, pp. 217-226.
  23. Shen, W., 2008, Building boundary extraction based on lidar point clouds data, International Archives Photogrammetry, Remote Sens., Spatial Info. Sci., Beijing, Vol. 37, part B3b, pp. 157-161.
  24. Shon, G., Jwa, Y. S., Tao, V., and Cho, W. S., 2007, Geometric regularization of irregular building polygons: a comparative study, Korean Journal of Geomatics, KSGPC, No. 25, Vol. 6-1, pp. 545-555.
  25. Xu, J., Y. Wan, and F. Yao, 2010, A method of 3d building boundary extraction from airborne lidar points cloud, IEEE 2010 Symposium on Photonics and Optoelectronic, IEEE.
  26. Weidner, U., and W. Forstner, 1995, Towards automatic building extraction from high-resolution digital elevation models, ISPRS Journal of Photogrammetry and Remote Sensing, ISPRS, 50, pp. 38-49. https://doi.org/10.1109/TGRS.2003.810682
  27. Zhang, K., S. Chen, D. Whitman, M. Shyu, J. Yan, and C. Zhang, 2003, A progressive morphological filter for removing nonground measurements from airbone LIDAR data, IEEE Transaction on Geoscience and Remote sensing, IEEE, Vol. 41, No. 4, 2003, pp. 872-882. https://doi.org/10.1109/TGRS.2003.810682

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