Geoscience Reference
In-Depth Information
Fig. 4 Seed point A grows
by adding adjacent elements
to its segmentation region
(Agathos et al.
2007
)
based on their semantic properties. This technique is able to segment a 3D model
directly in vector data format, making the result have a higher accuracy than
segmenting a raster data.
3.2.1 Semantic Segmentation
In order to preserve the semantic data during the segmentation process, first, the
3D building need to be segmented based on its semantic attributes. The semantic
data can be provided together in the CityGML file of the 3D building. Figure
5
shows a CityGML file that contains semantic data of the building.
In this phase, geometries that represent the semantic data will be differentiated
with each other, regardless the shapes they assembled. The segmented parts based
on the semantic also known as parent geometries. The child geometries will be
obtained using the segmentation technique based on the fitting primitives.
Even though the semantics are present in the CityGML structure, the proposed
segmentation method will classify the Wall Surface according to their semantic
information, recognized the objects as parent geometries and used it as a starting
point for geometric segmentation. Furthermore, it will enable the proposed method
to retain the semantic information of the child objects, which are inherited from the
parent geometries. If the model is not a semantic model, the segmentation method
will attempt to derive the semantic information based on user-predefined criteria for
certain features (if any) such as roof before proceeding with the geometric seg-
mentation. Figure
6
shows the result of the segmentation based on semantic-type.
3.2.2 Geometric Segmentation
Since the model has been segmented based on its semantics, the geometric seg-
mentation will start on each parent, instead of based on the whole model. Seg-
menting the parent geometries will allow complex shapes to be broken down to
