Environmental Engineering Reference
In-Depth Information
Since our method is a data-driven approach, we attempt the
reconstructed building models to approximate the given point
clouds the best. Compared to the model-driven methods, the
data-driven approach is more flexible. While the building model
reconstructed using the model-driven method is restricted by
a predefined catalog of buildings or building parts, a data-
driven approach requires more flexible assumptions. A typical
assumption in this study is that buildings can be modeled by
a composition of planar surfaces. However, this might be a
restriction, considering curved roof structures.
In our case study, due to the complexity and diversity of
natural and man-made objects in urban areas, manual input is
required in the classification stage, which reduces the automation
level. Another disadvantage is that those buildings partially cov-
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due to the failure of the roof detection, even these building areas
had been classified correctly. Finally, this study assumes a build-
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on methods for dealing with non-rectangular-shaped buildings
are needed. Nevertheless, the results met the requirement of
being accurate and reliable. Subsequent processing like texture
mapping is possible. The resulting models are well structured
and topologically correct and are, therefore, directly applicable
for 3D urban visualization.
In addition, for those applications requiring realistic 3D
city models, reconstructing photorealistic building facade mod-
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point clouds and close-range images. Considering quick cre-
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vehicle-borne mobile lidar mapping system would be an effec-
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along with color digital camera images of the roadside build-
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by both airborne and terrestrial mobile lidar mapping systems
would open a new avenue to reconstruction of realistic 3D
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Acknowledgments
The work presented in this chapter was supported by a NSERC
discovery grant and a Wiser Foundation research grant. The
datasets used in this chapter were provided by Optech, Inc.,
Toronto, Canada. The authors would like to thank the anony-
mous reviewers for their valuable comments.
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