Full text: Proceedings, XXth congress (Part 4)

  
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B4. Istanbul 2004 
  
  
Figure 12. Building region from 2D topographic map 
Table 2. Accuracy assessment for building detection 
  
  
  
  
  
  
  
  
  
  
  
  
Classified Data 
Unit: pixel | Building | Non Building | Total 
Building a=259685 | b-58176 e-317861 
«| Non Building c=17505 d=954895 f=972460 
Al Total g=277250 | h=1013071 1=1290321 
9 Diagonal Total 1214580 
5| Producer a/e=81% | d/f=98% 89.5% 
| User a/g=93% | d/h=94% 93.5% 
& Overall - - 94% 
(a+d)/i 
  
  
  
  
  
  
For each building region, the 3D planes are extracted by TIN- 
based region growing. Meanwhile, initial building edges are 
approximately detected in the DSM. The edges are then 
projected into aerial image to mark the working area for straight 
line detection. Through the Hough transform straight line 
extraction, the precise straight lines which combine the 3D 
planes can be projected into object space. After combining the 
3D lines with SMS method, the building model can be 
reconstructed. Comparing the coordinates roof corners in the 
reconstructed models with the corners measured from stereo: 
pairs, the root mean square errors are 0.45m, 0.56m, 0.70m in 
the X, Y, Z directions, respectively. The results of building 
models are shown in Figure 13. 
Figure 13. 3D view of generated building model 
6. CONCLUSIONS 
In this investigation, we have presented a scheme for the 
extraction of building regions and building modeling by 
performing fusion of LIDAR data and optical imagery. The 
results from the test show the potential of the automatic method 
for building reconstruction. More than 81% buildings region 
are correctly detected by our approach. The building models 
generated by the proposed method have the merits of high 
horizontal accuracy from aerial images and high vertical 
accuracy from LIDAR data. Comparing the models 
reconstructed by the proposed method with the reference data 
from aerial stereo pairs, we achieved sub-meter accuracy. 
However, in this investigation, we only consider flat roof 
buildings. The improvements of the scheme for treating more 
complex buildings are the major works in the future. 
REFERENCES 
Behan, A., 2000, On the matching accuracy rasterised scanning 
laser altimeter data. IAPRS, Vol. XXXIII, Part B2, pp.75-82. 
Briese, C., Pfeifer, N., and Dorninger, P., 2000, Application of 
the Robust Interpolation for DTM Determination. IAPRS, vol. 
XXXIILpp.55-61. 
Canny, J., 1986, A computational approach to edge detection, 
IEEE Transactions on Pattern Analysis and Machine 
Intelligence, Vol. PAMI-8, No. 6, pp. 679-698. 
Guo, T., 2003, 3D city modeling using high-resolution satellite 
image and airborne laser scanning data. Doctoral dissertation, 
Department of Civil Engineering, University of Tokyo, Tokyo. 
Hofmann, A.D., Mass, H., Streilein, A., 2002, Knowledge- 
based building detection based on laser scanner data and 
topographic map information, IAPRS, Vol.34, Part 3A+B, 
pp.163-169. 
Hough, P.V.C. 1962, Methods and means for recognising 
comples patterns, U.S. patent No. 306954 
Lohmann, P., 2002, Segmentation and filtering of laser scanner 
digital surface models, IAPRS, Vol. XXXIV, Part 2,, Xi'an,20- 
23, Aug, 2002, pp311-316 
736 
Intern 
  
Nakag 
Sterec 
3D Ut 
Rau, . 
buildi 
Photo, 
pp.18 
Rotter 
Buildi 
Part 4, 
Vosse 
aerial 
Geosc 
Toron 
Zhang 
image: 
filterir 
Vol.54
	        
Waiting...

Note to user

Dear user,

In response to current developments in the web technology used by the Goobi viewer, the software no longer supports your browser.

Please use one of the following browsers to display this page correctly.

Thank you.