Geoscience Reference
In-Depth Information
focused on developing an automated process for generating 3D city models Takase
et al. (
2003
), Sugihara and Hayashi (
2008
) and (Steinhage et al.
2010
). 3D building
generation process is important in change detection and analysis since it will
provide the input for the applications.
Isikdag and Zlatanova (
2010
) introduced an approach to draw and visualize
simple geometric representation of 3D buildings directly in the Google Earth
environment. Urban planning is known to be a complex and tedious process which
involves many parties and joint decision making. They suggested that by intro-
ducing this approach, all parties involved can easily access and view the data, and
get the better picture on the proposed structures and how it relates to the envi-
ronment on the actual site rather than just looking at the architectural model while
lacking on the information of the surrounding area.
Kim et al. (
2008
) presented a method to automatically generate Digital Building
Models (DBM) with complex structures (parts with different slopes, sizes, and
shapes) from LiDAR point clouds. The method consists of four steps. First, the
ground/non-ground points are classified based on the visibility analysis among
ground and non-ground points in a synthesized perspective view. Then, the non-
ground points are analysed and used to generate hypotheses of building instances
based on the point attributes and the spatial relationships among the points. Next,
each building is segmented into a group of planar patches. The intermediate
boundaries for segmented clusters are produced by using a modified convex hull
algorithm. These boundaries are used as initial approximations of the planar sur-
faces comprising the building model of a given hypothesis. Finally, those initial
boundaries are used to derive a refined set of boundaries, which are connected to
produce a wireframe representing the DBM.
The research done by Kim et al. (
2008
) provide an interesting idea on how to
automatically acquire a high quality 3D models with complex structures as an
input for detecting and analysing the changes that occurs on 3D building especially
for building management purposes.
2.3 3D Segmentation on 3D Buildings
3D model segmentation method has been used in various fields such as medical
technology, computer vision and geospatial applications. However, it serves the
same purpose which is to break down an object into simpler parts to be manip-
ulated for different applications such as object analysis, feature extraction and
classification, object recognition, model reconstruction and generalization.
Although most of the segmentation method used in geospatial and building-related
applications are based on 2D segmentation (Mian et al.
2006
; Tolt et al.
2006
;
Miliaresis and Kokkas
2007
; Sampath and Shan
2010
; Cheng et al.
2010
), there are
some researches that dwelled into the 3D segmentation as presented by You et al.
(
2003
), Hu et al. (
2004
), Thiemann and Sester (
2004
), Poupeau and Bonin (
2006
)
and, Manferdini and Remondino (
2010
).
