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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B3. Istanbul 2004
buildings. The third part is a high-density built-up area with EEE P
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groups of connected, complex rooftops, and less-orthogonal Diele] (rie) alsin] ceder s of UN Ctm
buildings. The number of measured roof-edges is 6,363. Figure EM me GOV DUE
4 depicts the reconstructed polyhedral building models for this
data set displayed using the 3-D visualization tool. The number
of roof-primitives created using the SMS method was 1,809.
The splitting and merging process was totally successful after
the correction of blunder measurements. However, 38
roof-primitives failed at the shaping stage, giving a success rate
of 98%. The 2% failure rate was totally recovered using the
provided post-processing functions, without any manually
editing of building models.
Figure 6. a - Simple gable roof.
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inuixi
Figure 4. The generated 3D building model based on manual
stereo measurement of visible roof-edges.
3.2 Semi-Automatic Measurement of Visible Roof-Edges
In order to evaluate the proposed interactive scheme, we
demonstrate three case studies using the above four-views aerial
photos. Figure 5,6,7 depict those case studies with one flat roof
and two gable roofs. Figure 8 illustrates the generated 3D
building models.
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Figure 8. Reconstructed 3D building models.
3.3 Accuracy Assessment
The accuracy of the generated building models mostly depends
on the accuracy of the measurements. For manual measurement,
the total number of visible corners being evaluated is 163. After
applying the SMS method for building modelling, it achieves a
MEAN error of 1.06 cm, 1.22 cm, and 2.73 cm on the X, Y and
Z-axis, respectively. In the mean time, a Root-Mean-Square
Error (RMSE) of 13.5 cm, 14.5 cm, and 34.9 cm on the X, Y and
Z-axis, respectively, is achieved. Since the original stereo-pair
has a nominal ground sampling distance of 12.5 cm and a
base-height-ratio of 0.3, the RMSE is close to be one pixel on
the image scale, which falls into the range of random errors. It is
proven that the proposed SMS method is accurate in 3D
building modelling.
-
For semi-automatic approach, the feature line extraction and
stereo matching will introduce a certain degree of error. For
above three case studies, the overall accuracy is about 0.292 and
587
