The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B4. Beijing 2008 
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4. CONCLUSIONS 
An automatic solution for DBM generation for complex 
structures from raw LiDAR data is introduced through four 
main procedures: ground/non-ground point separation; building 
hypothesis generation; segmentation of planar patches and 
intermediate boundary generation; and boundary refinement 
and 3D wire frame generation. First, a robust ground/non 
ground point classification technique is proposed based on the 
novel idea of detecting points that produce occlusions. A 
building hypothesis generation procedure is devised based on 
the geometric characteristics of man-made structures. A 
segmentation procedure which simultaneously considers 
similarity attributes and proximity in the object space to derive 
robust and accurate solution was then performed. In the last step 
of the proposed methodology, several geometric constraints are 
applied to delineate the boundaries and to construct 3D wire 
frames for complex structures. The experimental results prove 
that the proposed methodology can provide a relatively accurate 
solution from raw LiDAR data. Moreover, it is proved that the 
limitation of the LiDAR data resolution causes deterioration of 
the accuracy of DBM as well as loss of details, especially for 
complex man-made structures. The limitations of the LiDAR 
data in the generation of DBM can be overcome by 
incorporating high resolution imagery into the procedures. 
More rich semantic information from high resolution imagery 
will help to improve the accuracy of the DBM and to detect 
edge details of buildings. Therefore, further research on the 
integration of LiDAR data and imagery will be investigated as 
future work. 
ACKNOWLEDGEMENT 
We would like to thank the GEOIDE (GEOmatics for Informed 
DEcisions) Network of Centers of Excellence of Canada 
(SII#43) and ETRI (Electronics and Telecommunications 
Research Institute) for their partial financial support of this 
research. 
REFERENCES 
Brenner, C., and Haala, N. (1998). Rapid acquisition of virtual 
reality city models from multiple data sources, International 
Archives of Photogrammetry and Remote Sensing, 32(5): 323- 
330. 
Brunn, A., and U.Weidner, 1997. Extracting building from 
digital surface models, International Archives of 
Photogrammetry and Remote Sensing, 34(3-4): 27-34. 
Ameri, B. , 2000. Automatic recognition and 3D reconstruction 
of buildings from digital imagery, Deutsche Geodaetische 
Kommission, Series C, No. 526. 
Chang, Y.., C. Kim, A. Kersting, and A. Habib, 2007. New 
approach for DTM generation from LiDAR data, The 28th 
Asian Conference on Remote Sensing (ACRS), Kuala 
Lumpur, Malaysia, (Nov. 12-16,2007). 
Douglas, D.H., and T.K. Peucker, Algorithms for the reductions 
of the number of points required to represent a digitized line or 
its caricature, The Canadian Cartographer 10(2), pp. 112-122 
(1973). 
Filin, S., Pfeifer, N., 2006. Segmentation of airborne laser 
scanning data using a slope adaptive neighborhood. In: ISPRS 
Journal of Photogrammetry & Remote Sensing, 60, pp. 71-80. 
Haala, N., Brenner, C., and Anders, K.-H. (1998). 3D urban 
GIS from laser altimeter and 2D map data, International 
Archives of Photogrammetry and Remote Sensing, 32(3/1): 339- 
346. 
Habib, A., E. Kim, and C. Kim, 2007. New methodologies for 
true orthophoto generation, Photogrammetric Engineering and 
Remote Sensing, 73(1), pp. 25-36. 
Habib, A., Y. Chang, D. Lee. Occlusion-Based Methodology 
for the Classification of LiDAR Data, Photogrammetric 
Engineering & Remote Sensing Submitted on January 25, 2008 
Jarvis, R. A., 1977. Computing the shape hull of points in the 
plane, Proceedings of IEEE Computer Society Conference 
Pattern Recognition and Image Process, pp.231-261 
Rottensteiner, F., and C. Briese, 2002. A new method for 
building extraction in urban areas from high resolution lidar 
data, Proceedings of the ISPRS Commission III Symposium, 
Graz, Austria, unpaginated CD-ROM. 
Vosselman, G., and S. Dijkman, 2001. 3D building model 
reconstruction from point clouds and ground plans, 
International Archives of Photogrammetry and Remote Sensing, 
34(3W4): 37-43.