Korean Journal of Remote Sensing (대한원격탐사학회지)

Korean Society of Remote Sensing (대한원격탐사학회)
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Building Extraction from Lidar Data and Aerial Imagery using Domain Knowledge about Building Structures

  • Seo, Su-Young (GeoResources Institute, Mississippi State University)
  • Published : 2007.06.30
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Abstract

Traditionally, aerial images have been used as main sources for compiling topographic maps. In recent years, lidar data has been exploited as another type of mapping data. Regarding their performances, aerial imagery has the ability to delineate object boundaries but omits much of these boundaries during feature extraction. Lidar provides direct information about heights of object surfaces but have limitations with respect to boundary localization. Considering the characteristics of the sensors, this paper proposes an approach to extracting buildings from lidar and aerial imagery, which is based on the complementary characteristics of optical and range sensors. For detecting building regions, relationships among elevation contours are represented into directional graphs and searched for the contours corresponding to external boundaries of buildings. For generating building models, a wing model is proposed to assemble roof surface patches into a complete building model. Then, building models are projected and checked with features in aerial images. Experimental results show that the proposed approach provides an efficient and accurate way to extract building models.

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References

  1. Abidi, M. A. and R. C. Gonzalez, 1992. Data Fusion in Robotics and Machine Intelligence, Academic Press, San Diego, 546 p
  2. Ameri, B., 2000. Automatic Recognition and 3D Reconstruction of Buildings Through Computer Vision and Digital Photogrammetry, Ph.D. Dissertation, University of Stuttgart, Stuttgart, Germany, 110 p
  3. Baltsavias, E. P., S. O. Mason, and D. Stallmann, 1995. Use of DTMs/DSMs and orthoimages to support building extraction, Automatic Extraction of Man-Made Objects from Aerial and Space Images (A. Grun, O. Kubler, and P. Agouris, editors), Birkaeuser, Basel, pp.199-210
  4. Baillard, C., O. Dissard, O. Jamet, and H. Maitre, 1998. Extraction and textural characterization of above-ground areas from aerial stereo pairs: a quality assessment, ISPRS Journal of Photogrammetry and Remote Sensing, 53(2): 130-141 https://doi.org/10.1016/S0924-2716(97)00036-1
  5. Brunn, A. and U. Weidner, 1998. Hierarchical Bayesian nets for building extraction using dense digital surface models, ISPRS Journal of Photogrammetry and Remote Sensing, 53(5): 296-307 https://doi.org/10.1016/S0924-2716(98)00012-4
  6. Csatho, B., W. Krabill, Lucas, J., and T. Schenk, 1998. A multisensor data set of an urban and coastal scene, International Archives of Photogrammetry and Remote Sensing, 32(Part 3/2): 26-31
  7. Csatho, B., T. Schenk, D.-C. Lee, and S. Filin, 1999. Inclusion of multispectral data into object recognition, International Archives of Photogrammetry and Remote Sensing, 32(Part 7-4-3 W6): 53-61
  8. Brenner, C. and N. Haala, 1998. Fast production of virtual reality city models, IAPRS Commission IV Symposium on GIS, Stuttgart, Germany, pp. 77-84
  9. Brunn, A., E. Gulch, F. Lang, and W. Foestner, 1998. A hybrid concept for 3D building acquisition, ISPRS Journal of Photogrammetry and Remote Sensing, 53(2): 119-129 https://doi.org/10.1016/S0924-2716(97)00039-7
  10. Fischer, A., T. H. Kolbe, Lang F., A. B. Cremers, W. Foestner, L. Plumer, and V. Steinhage, 1998. Extracting buildings from aerial images using hierarchical aggregation in 2D and 3D, Computer Vision and Image Understanding, 72(2): 185-203 https://doi.org/10.1006/cviu.1998.0721
  11. Fischler, M. A. and R. C. Bolles, 1981. Random sample consensus: A paradigm for model fitting with application to image analysis and automated cartography, Communications of the ACM, 24(6): 381-395 https://doi.org/10.1145/358669.358692
  12. Haala, N. and C. Brenner, 1999. Extraction of buildings and trees in urban environments, ISPRS Journal of Photogrammetry and Remote Sensing, 54: 130-137 https://doi.org/10.1016/S0924-2716(99)00010-6
  13. Jaynes, C., E. Riseman, and A. Hanson, 1997. Building reconstruction from optical and range images, Computer Vision and Pattern Recognition, San Juan, Puerto Rico, pp. 374- 379
  14. Lee, I. and T. Schenk, 2001. 3D perceptual organization of laser altimetry data, International Archives of Photogrammetry and Remote Sensing, 34(Part 3/ W4): 57-65
  15. Liu, X. and J. Ramirez, 1997. Automated vectorization and labeling of very large hypsographic map images using a contour graph, Surveying and Land Information Systems, 57(1): 5-10
  16. Mckeown, D. M., S. D. Cochran, S. J. Ford, J. C. McGlone, J. A. Shufelt, and D. A. Yocum, 1999. Fusion of HYDICE hyperspectral data with panchromatic imagery for cartographic feature extraction, IEEE Trans. on Geoscience and Remote Sensing, 37(3): 1261-1271 https://doi.org/10.1109/36.763286
  17. Rousseeuw, P. J., 1984. Least median of squares regression, Journal of the American Statistical Association, 79(388): 871-880 https://doi.org/10.2307/2288718
  18. Schenk, T. and B. Csatho, 2002. Fusion of LIDAR data and aerial imagery for a more complete surface description, International Archives of Photogrammetry and Remote Sensing, 34(Part 3A): 310-317
  19. Seo, S., 2003. Model-Based Building Extraction from LIDAR and Aerial Imagery, Ph.D. Dissertation, The Ohio State University, Columbus, Ohio, 138 p
  20. Seo. S. and T. Schenk, 2003. A study of integration methods of aerial imagery and LIDAR data for a high level of automation in 3D building reconstruction, Proceedings of the SPIE, 5099: 65-76
  21. Tao, G. and Y. Yasuoka, 2002. Combining high resolution satellite imagery and airborne laser scanning data for generating bareland DEM in urban areas, International Archives of Photogrammetry and Remote Sensing, 34(Part 5/W3), unpaginated CD-ROM
  22. Vosselmann, G. and S. Dijkman, 2001. 3D building model reconstruction from point clouds and ground plans, International Archives of Photogrammetry and Remote Sensing, 34(Part 3/W4): 37-43
  23. Wang, Z., 1998. Extracting building information from LIDAR data, International Archives of Photogrammetry and Remote Sensing, 32(3/1): 279-284
  24. Wu, C.-H., 1993. Automated Identification of Scanned Contour Information for Digital Elevation Models, Ph.D. Dissertation, University of Maine, Orono, Maine, 120 p