航照影像與光達點雲所含的幾何資訊具有互補性質，空載影像具有良好的地物邊界線但高程資訊較內隱，反之，光達點雲含有準確的高程資訊但地物邊界較不明確。本篇研究提出利用空載光達資料及單張航照影像重建三維房屋模型。由於多數房屋具規則幾何外型，本研究以重建由平面所組成的房屋為主。
本研究工作包含五個部分: (1)屋頂面組成，(2)屋頂面分類，(3)結構線定位，(4)二維線段組成以及(5)三維房屋模型重建。將屋頂上的光達點雲萃取出並利用共面分析組成屋頂面，再使屋頂面分類成，平頂屋頂、多斜面屋頂以及單斜面屋頂。然而，光達點雲具有誤差，對於由緩斜面組成的多斜面屋頂，緩斜面難以偵測。因此，本篇利用漸進式的搜取法分析光達點雲求得最佳的斜面。之後，利用屋頂面的資訊獲得初始邊界線以及屋頂結構線的區間。將物空間所求得的初始邊界線反投影至像空間建立工作區，於工作區中進行直線偵測並組成屋頂結構線段以及候選邊界線段。精確的邊界線段萃取後再將組成的線段投影回物空間以重建三維房屋模型。
以實際量測之房屋模型與研究結果所產生的模型比較以驗證成果的精確度。測試資料包括: (1)航照DMC 影像，空間解析度為16 公分以及(2) 空載光達掃描系統：Leica ALS 50 之光達點雲資料，點雲密度為10 points/m²。所得成果品質之誤差於X方向為±0.242公尺、Y方向為±0.246公尺以及Z方向為±0.260公尺。

Aerial imagery and lidar point clouds are complementary in terms of geometric information
contents. Aerial imagery has good definition of object edges but the information of object
elevation is implicit. Lidar point clouds, on the other hand, explicitly record the 3D
information of scanned object points but object edges are less clear than that in an aerial
imagery. This study proposes a method that integrates single imagery and lidar point clouds to
reconstruct 3D building models. Most buildings have multi-facet shapes, so that this paper
mainly focuses on the reconstruction of polyhedral buildings.
The proposed scheme is composed of five major parts, (1) Segmentation of Roof Patches, (2)
Roof Patch Classification, (3) Determination of Structure Lines, (4) 2D Line Segmentation,
and (5) 3D Building Model Reconstruction. The roof patches were segmented via the
coplanirity analysis with the lidar points on the roofs. Then, the roof patches were classified
into flat, multi-pitched and mono-pitched roof patches. Considering the errors of Lidar data,
the localization of low-pitched roofs from multiple slope ones could be difficult. Thus, we
analyzed the point clouds to find the optimal roof patches progressively. Once the patches
were found, we determined the initial building boundaries and the zones of roof structure lines
in the third step. The initial boundaries and the zones of roof structure lines were then
projected to the image space for the determination of a work area. Next, we detected the edges
in the working areas to find the edges and vectorized the edges to form the roof structure line
iii
segments and candidate boundaries segments. The refined boundaries were extracted and then,
the line segments were projected to object space to reconstruct 3D building models.
The accuracy of the results was validated by examining the discrepancy between the manually
measured building models and generated ones. The test data included (1) DMC aerial imagery
with a spatial resolution of 16 cm, and (2) Lidar point clouds from Leica ALS 50. Experiment
results indicate that the accuracies are ±0.242m in X-dir, ±0.246m in Y-dir, and ±0.260m in
Z-dir.

Akel, N.A., Filin, S., and Doytsher, Y., 2009, Reconstruction of Complex Shape Buildings from LiDAR Data Using Free Form Surfaces. Photogrammetric Engineering and Remote Sensing, 75(3), pp.271-280.
Baillard, C., Schmid, C., Zisserman, A., and Fitzgibbon, A., 1999, Automatic line matching and 3D reconstruction of buildings from multiple views. International Archives of Photogrammetry and Remote Sensing, 32, Part 3-2W5, 69–80.
Barber, C.B., Dobkin, D.P., and Huhdanpaa, H.T., 1996, The Quickhull Algorithm for Convex Hulls. ACM Transactions on Mathematical Software, 22(4), pp. 469-483.
Brenner, C., 2005, Building reconstruction from images and laser scanning. Int. J. Appl. Earth Obs. Geoinf., vol. 6, no. 3/4, pp. 187–198.
Canny, J., 1986, A Computational Approach to Edge Detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, 8(6), pp. 679-698.
Chen, L.C. and Lee, L.H., 1992, Progressive generation of control frameworks for image registration. Photogrammetric Engineering and Remote Sensing, 58(9), pp. 1321–1328.
Chen, L.C., Teo, T.A., Kuo, C.Y., and Rau, J.Y., 2008, Shaping polyhedral buildings by the fusion of vector maps and lidar point clouds. Photogrammetric Engineering and Remote Sensing, 74 (9), 1147–1157.
Cheng, L., Gong, J., Li, M., and Liu, Y., 2011, 3D Building Model Reconstruction from Multi-view Aerial Imagery and Lidar Data, Photogrammetric Engineering & Remote Sensing, 77(2), pp. 125-139.
Durieux, L., Lagabrielle, E., and Nelson, A., 2008, A method for monitoring building construction in urban sprawl areas using object-based analysis of Spot 5 images and existing GIS data. ISPRS Journal of Photogrammetry and Remote Sensing, 63 (4), pp.399-408.
Filin, S. and Pfeifer, N., 2005, Neighborhood systems for airborne laser data. Photogrammetric Engineering and Remote Sensing, 71, pp. 743-755.
Forlani, G., Nardinocchi, C., Scaiono, M., and Zingaretti, P., 2006, Complete classification of raw LIDAR and 3D reconstruction of buildings. Pattern Anal. Appl., 8(4), pp. 357–374.
Ghilani, C. & Wolf, P., 2006, Adjustment Computation-Spatial Data Analysis (4th ed.), New Jersey: Wiley, J. & Sons, Inc., pp. 334.
Golias, N.A. and Dutton, R.W., 1997, Delaunay Triangulation and 3D Adaptive Mesh Generation, Finite Element in Analysis and Design. 25, pp. 331-341.
Haala, N. and Kada, M., 2010, An update on automatic 3D building reconstruction, ISPRS Journal of Photogrammetry and Remote Sensing 65, pp. 570–580.
Habib, A., Lee, Y., and Morgan, M., 2003, Automatic matching and three-dimensional reconstruction of free-form linear features from stereo images. Photogrammetric Engineering & Remote Sensing, 69(2), pp.189–197.
Habib, A.F., Zhai, R., and Kim, C., 2010, Generation of complex polyhedral building models by integrating stereo-aerial imagery and LiDAR data. Photogrammetric Engineering & Remote Sensing , 76 (5), pp.609–623.
Harris, C. and Stephens, M., 1988, A combined corner and edge Detector. In Fourth Alvey Vision Conference, Manchester, UK, pp. 147-151.
Hirschmüller, H., 2006, Stereo processing by semiglobal matching and mutual information. PAMI, 30(2), pp. 328–341.
Hofmann, A.D., 2004. Analysis of TIN-structure parameter spaces in airborne laser scanner data for 3-D building model generation, IAPRS, 35(B3) , pp. 302-307.
Hough, P.V.C., 1962, Methods and Means for Recognizing Complex Patterns. U.S. patent No. 3069654.
Hu, J., You, S., and Neumann, U., 2006, Integrating lidar, aerial image and ground images for complete urban building modeling. 3DPVT’06, pp. 184–191.
Jwa, Y., Sohn, G., Tao, V., and Cho, W., 2008, An implicit geometric regularization of 3d building shape using airborne lidar data. International Archives of Photogrammetry and Remote Sensing, Beijing, China, XXXVI, 5, pp. 69–76.
Kim, C., Habib, A., and Chang, Y., 2008, Automatic generation of digital building models for complex structures from LiDAR data. International Archives of Photogrammetry and Remote Sensing, 37, pp.456-462.
Kim, Z., and Nevatia, R., 2004, Automatic description of complex buildings from multiple images. Computer Vision and Image Understanding, 96 (1), pp. 60-95.
Lue, Y., 1988, Interest Operator and Fast Implementation. International Archives of Photogrammetry and Remote Sensing, 27 (B3), pp.491-500.
Mortenson, Michael E., 1999, Mathematic for Computer Graphics Application, Industrial Press, New York, 2nd edition, pp.202-204.
OEEPE, 1996. OEEPE - Survey on 3D-City Models
http://www.ipb.uni-bonn.de/OEEPE/oeepe.html: (Last accessed 2 Jan, 2008)
Ok, A.O., Wegner, J.D., Heipke, C., Rottensteiner, F., Soergel, U., and Toprak, V., 2010, A Stereo Line Matching Technique For Aerial Images Based on A Pair-Wise Relation Approach, International Archives of Photogrammetry and Remote Sensing, 38(1/W17), Istanbul (on CD-ROM).
Portalés, C., Lerma, J.L. and Navarro, S., 2010, Augmented reality and photogrammetry: A synergy to visualize physical and virtual city environments. ISPRS Journal of Photogrammetry & Remote Sensing, 65(1), pp. 134-142.
Rau, J. Y., and Chen, L. C., 2003, Robust reconstruction of building models from three-dimensional line segments, Photogrammetric Engineering and Remote Sensing, 69, pp. 181-188.
Ranzinger, M. and Gleixner, G., 1997, GIS-datasets for 3D urban planning, computers. Environ. Urban Syst, 21 (2), pp. 159-173.
Rottensteiner F., Briese C., 2002, A new method for building extraction in urban areas from high-resolution LIDAR data. International Archives of Photogrammetry and Remote Sensing, 34(3A), pp. 295-301.
Sampath, A. and Shan, J., 2007. Building boundary tracing and regularization from airborne LiDAR point clouds. Photogrammetric Engineering & Remote Sensing, 73 (7), pp. 805–812.
Sampath, A., Shan, J., 2010. Segmentation and reconstruction of polyhedral building roofs from aerial LiDAR point clouds. IEEE Transactions on Geoscience and Remote Sensing, 48 (3), pp. 1554–1567.
Schwalbe, E., Maas, H.-G. and Seidel, F., 2005. 3D building model generation from airborne
laser scanner data using 2D GIS data and orthogonal point cloud projections. International Archives of Photogrammetry and Remote Sensing, 36(3/W36), pp. 209-214.
Sırmaçek, B. and Ünsalan, C., 2008, Building detection from aerial imagery using invariant color features and shadow information. In International Symposium on Computer and Information Sciences, Istanbul, Turkey.
Sohn, G. and Dowman, I., 2007, Data fusion of high-resolution satellite imagery and LiDAR
data for automatic building extraction. ISPRS Journal of Photogrammetry and RemoteSensing, 62(1), pp. 43-63.
Sonka, M., Hlavac, V., and Boyle, R., 1999, Image Processing, Analysis, and Machine Vision, 2nd ed. Albany, NY: Brooks/Cole.
Suveg, I., 2003, Reconstruction of 3D building models from aerial images and maps. Delft
University of Technology, Delft, The Netherlands, pp. 143.
Teo, T.A., Chen, L.C., Liu, J.K., and Hsu, W.C., 2005. Building reconstruction From Lidar Data Using Iterative Regularization Approach, Proceedings of Asian Conference on Remote Sensing, Nov. 7-11, Hanoi, Vietnam, CD-ROM.
Teo, T.A., 2008, A Divide-and-Conquer Strategy for Building Reconstruction Using Lidar Point Clouds and Topographic Maps. Ph.D. Dissertation, National Central University, Taiwan.
Tseng, Y.H. and Wang, S., 2003, Semiautomated building Extraction Based on CSG Model-Image Fitting, Engineering Remote Sensing, 69, pp. 171–180.
Verma, V., Kumar, R., and Hsu, S., 2006, 3D building detection and modeling from aerial lidar data. CVPR 2006, 2, pp. 2213–2220.
Zhang, L. and Grü, N. A., 2006, Multi-image matching for DSM generation from IKONOS imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 60, pp. 195–211.
Zhao, F., Huang Q., and Gao, W., 2006, Image Matching by Normalized Cross-Correlation. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing ICASSP2006, 2, pp. II-II, 14-19.