ISPRS Commission III, Vol.34, Part 3A „Photogrammetric Computer Vision“, Graz, 2002
Figure 2-d. The Candidate Building Points
(Building 2)
For each building candidate point a window is constructed
around the point. All candidate points in the window are used
to fit a plane using Equation (1). For each candidate point
nine positions were tried and the position with the minimum
residual was selected. This helps to include corner points and
edge points, where the candidate point is either in the
window corner or on its edge. A linear least squares
estimation approach (Mikhail, er. a]. 2001) is used to find the
plane parameters at each point. If a statistic representing
misclosure is small, the plane parameters at this point are
used to vote in the 2D parameter space. Figure 3a and b
show the parameter space for the two buildings previously
illustrated.
The window size and the parameter space cell size are based
on the quality of the LIDAR data and the building
characteristics. Poor quality data forces the cell size to be
large in order to compensate for variation in the evaluated
parameters of different points in the same plane. The
relationship between points and their associated parameter
cell is preserved for later use. The approach is similar to that
used in Davies et. al. (1988) to extract straight lines.
Figure 3-a. The Parameter Space (Building 1)
A- 104
Figure 3-b. The Parameter Space (Building 2)
The parameter space is then searched to find peak cells. Cells
with a high number of contributing points are identified and
used as the building planes. The minimum number of points
in the cell to be used as the threshold varies depending on the
data quality, building size, and DEM resolution. Each cell is
then given an identification number to identify this plane.
Points that contribute to a certain plane are then categorized
using their plane identification number. Plane regions are
then extracted using the identification number. Each point in
the DEM has its plane identification number. We used a
region- growing algorithm (Jain, 1989) to connect points with
the same identification number. Regions with small areas are
then eliminated, while other regions are kept as the building
roof regions. Holes in the roof regions are then filled. Figure
4-a and b show the extracted roof regions. The roof regions
are used to extract the roof boundaries in the next section.
Figure 4-a. Extracted Roof Regions (Building 1)