(h) 
second building 
f different MBR 
from the LiDAR 
g the sequential 
t levels (red and 
he final adjusted 
ed onto the image. 
aerial images that 
s no limitation in 
of a single image 
he use of more 
building which 
    
  
T n (b) 
Figure 6. Initial MBRs (a) and adjusted MBRs (b) of the first 
building projected onto the image 
As seen in Figure 5, three MBR levels are derived from the 
second test building. The three levels of initial models and 
their adjustment results are depicted in Figure 7 where the 
different colors represent the different MBR levels. 
   
(a) (b) 
Figure 7. Initial MBRs (a) and adjusted MBRs (b) of the 
second building projected onto the image 
At last, the final shape of each building which is the result 
from the Boolean operation of the adjusted MBRs is 
projected onto the image (Figure 8). 
  
Figure 8. Final shape of the building projected onto the image 
4. CONCLUSIONS AND FUTURE WORK 
This paper presented a robust approach to generate building 
models automatically from LiDAR and imagery by proposing 
the recursive MBR and the sequential MBR adjustment. 
Experimental results demonstrate how the recursive MBR 
algorithm decomposes buildings into rectangular models 
automatically and models are adjusted sequentially. The final 
model can be achieved by alternating the Boolean operation 
of subtraction and addition from each level of adjusted MBRs. 
This methodology can be applied to more complex buildings 
With more MBR levels. While the proposed approach 
provides high level of automation and accuracy, it can model 
only the types of buildings which decompose into rectangles. 
Future work includes increasing the applicability of the 
proposed algorithm for other building shapes in order to 
obtain complete building models and maintain the high 
accuracy and automation level. 
ACKNOWLEDGEMENTS 
This work was supported by the Canadian GEOIDE NCE 
Network (IV-17) and the National Science and Engineering 
Council of Canada (Discovery Grant). The authors would 
like to thank McElhanney Consulting Services Ltd, BC, 
Canada for providing the real dataset and technical feedback. 
Last but not least, this work could not be accomplished 
without the help of Zahra Lari and Ivan Detchev. 
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