• Stronger contrast by geometries than optical factors (illumi 
nation, color pattern, etc.). 
Some limitations of the current refinement method have been lo 
cated at: 
It cannot solve ambiguities caused by multiple lines with 
similar geometry properties. 
It cannot distinguish whether a model-image inconsistency 
is caused by reconstruction errors or inaccurate exterior ori 
entation. 
Knowledge based reasoning of the image information is the key 
to the first problem. The current matching stretchy is rather local. 
Experiments show that the offset direction between the model 
edges and their matched image lines are mostly same, which 
is obviously caused by inaccurate exterior orientation. A globe 
matching process (RANSAC over offsets for example) should be 
able to estimate the correct exterior orientations. 
7 CONCLUSIONS AND OUTLOOK 
In this paper we present a model refinement method, which uses 
the lines extracted from close-range images to improve building 
models reconstructed from terrestrial laser point clouds. With 
the refinement, several modeling errors caused by either gaps in 
laser data or reconstruction algorithm, are corrected with image 
information. Texturing is also improved after the refinement. 
Nowadays it is more and more common for acquisition platforms 
to acquire laser data and optical data simultaneously. Line ex 
traction from images is very accurate, while laser points are more 
suitable to extract planar features. Efficient fusing of laser points 
and image naturally avoids many barriers for building reconstruc 
tion from either sides. The attempt through our refinement method 
shows promising future for automated building reconstruction by 
fusing laser altimetry and optical methods. 
Two directions of the future work: knowledge based image rea 
soning and global matching, have been suggested earlier. Be 
sides, nowadays the mainstream image acquisition systems usu 
ally determine exterior orientations via GPS and IMU, but they 
are not accurate. If we use the laser points as reference data, 
and match image lines with model edges from laser point clouds 
(similar to this research), there should be enough control points 
for estimating the accurate exterior orientations for images. 
ACKNOWLEDGEMENTS 
The authors would like to thank Cyclomedia B.V. for providing 
the Cyclorama data. 
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