El-Hakim, Sabry
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Figure 2: Summary of the overall procedure
2.2.1 Registration of Main Images. The images are displayed in the proper order and common points are extracted and
labeled interactively. If correct scale is required, some distances in the scene are also measured. Control points, if
available, or data from positioning devices (e.g. GPS), may also be utilized in this step. A bundle adjustment is carried
out to register the images. In addition to registered images, we also have a number of unorganized scattered 3D points.
2.2.2 Segmentation, Fitting, and Automatic Point Densification. The 3D points generated so far are not sufficient for
modeling. They are also unorganized, thus the connectivity, or the topology, is unknown. Three interrelated operations
are needed in order to add sufficient points and organize them to create a complete 3D model. Segmenting or grouping
3D points into sets each belonging to a different surface is the first step. Most existing automatic modeling methods
were developed for organized 3D points, such as the range images obtained from a laser scanner [Soucy et al, 1996], or
unorganized points belonging to specific types of object [Hoppe et al, 1992]. Unorganized points obtained from features
on various surfaces on different objects are almost impossible to model automatically since they are subject to many
possible interpretations. In our approach, the scene is visually divided into surface patches, each is triangulated and
texture mapped separately. Although this is specified manually by a human operator, it is easy to do since all that is
required is to draw, with the mouse, a window around the points belonging to the same surface set. Once this is done,
the modeling will be carried out fully automatic. Each set may be on a different surface, or the same surface may be
divided into several sets depending on the complexity of its shape.
(A) (B)
Figure 3: Using existing features to fit a known shape (sphere) then automatically adding any number of points.
Using any existing features on the surface set, 3D-point computation is first done interactively [Figure 3.A]. These 3D-
points are then used to compute the function defining the surface, using least squares fitting. The function is in turn used
to automatically generate new points on the surface [Figure 3.B, half with texture]. On more complex surfaces, we can
only interpolate between the existing triangles by a subdivision technique [Zorin, 1997]. For partially occluded surfaces,
a single image can be used to extend the surface. For example, in figure 4, we can extend the floor (4.A) or the side of
206 International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B5. Amsterdam 2000.
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