of feature points include geometric and radiometric properties. 
The geometric properties of a feature point include its location 
in the image, the number of edges which intersect at the point 
and their spatial directions, angles between the edges and the 
locations of points which connect with the current point. The 
radiometric properties include the average intensity value 
between two edges. 
The feature relations include topological relations between 
edges and between points and edges. Intersecting edges are 
arranged clockwise based on their spatial orientation. Their 
relation can be represented by left and right while the relation 
between a point and an edge can be described by connect-to. 
3.2 Matching of Roof Points 
After feature points are extracted from both vertical and oblique 
images and their properties and relations are determined, they 
are matched to generate 3D feature points. Due to the nature of 
oblique images, the background around a feature point is quite 
different in different images. Therefore a feature-based image 
matching method instead of an area-based image matching is 
used to find the corresponding feature points on the overlapping 
images. Each feature point is represented as the intersection of 
two or more than two edges. Corresponding feature point in the 
overlapping images should be the intersection of corresponding 
edges if they are visible in the images and are extracted. Thus, 
the criteria used in the image matching are the spatial directions 
of edges associated with the feature point and the gray value 
between two edges. The point with minimum difference of edge 
direction and gray value is treated as the corresponding point. 
Since image matching is done among the vertical and four 
oblique images with different view directions, usually a feature 
point can be matched on more than three images. Once a point 
is matched successfully, its coordinates in ground coordinate 
system are computed by the least square adjustment method. 
After the ground coordinates are calculated, the residuals of the 
point can be computed on all the images and the points with 
large residuals are treated as unreliable point and removed, and 
the matched points on the remaining images are used to 
. compute the point's coordinates again. Finally, the point’s 
elevation is checked against the terrain's elevation around the 
point and the point is kept if the elevation difference is larger 
than the given threshold. One example of matched roof points 
is shown in Figure 3. 
  
(a) (b) 
Figure 3. Matched roof points (a) matched roof points on nadir 
image (b) matched roof points on oblique image with North 
view 
333 Grouping of Roof Points 
In grouping, the generated 3D feature points belonging to the 
same roof facets are grouped together to create roof facets. The 
   
grouping starts with any feature point and one edge associated 
with the point as point a, and edge /, shown in Figure 4. It 
proceeds to the next point using the relation connect-to and 
finds the next edge by relation right (a; and /). This process is 
repeated until it reaches at the starting point. Once all feature 
points of the facet are found, a plane is fitted to the points by 
the least squares adjustment. If the facet has more than three 
roof points, the elevation of every point will be checked against 
the fitted plane. The elevation of a point will be corrected if the 
difference between the fitted surface and the point is larger than 
the given threshold. In this way, all roof facets are created. 
(a adi e 03 
in 
f^ 
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Figure 4. Grouping of feature points 
4. TESTS RESULTS 
To test the developed approach, a number of images have been 
tested. The test images are color image data captured by 
Pictometry's imaging system. Each group of test images have 
one nadir image and four oblique images with different view 
directions, i.e. north, south, east and west. The nadir images 
have a GSD of 10 cm (4") while the GSD of oblique images is 
between 10 cm and 13 cm within the image. The areas covered 
by the test images are typical residential area and most 
buildings in the areas are two story residential buildings. Some 
of the test results are listed in Table 1. 
  
  
  
  
  
  
No. of Type of Number of Number of 
building building roof facets extracted roof 
facets 
1 Hip 4 4 
2 Complex 10 10 
3 Complex 11 11 
4 Complex 15 13 
5 Complex 30 25 
  
  
  
  
  
  
Tablel. Results of building extraction 
The first test building in the table is a residential building with 
hip roof as shown in Figure 5. This is a typical simple 
residential house. The reconstruction of this type of building is 
relatively easy since they have very simple roof structure. The 
only issue with this building is that there is a deck on one side 
of the building and there are some decorations around the 
building. This needs to be dealt with carefully. The result shows 
that four roof facets were extracted successfully. 
The second test building is a two story residential building with 
combined hip and gable roof structure. The roof has ten roof 
facets and each has a reasonable size. Most facets have simple 
  
  
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