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To substitute this order-relation for the edges of the triangula-
tion, Choi uses the given distinct point. In our approach
another - more intrinsic - property of the surface is utilized: the
surface-normal in the data-points.
With the use of the normal a left/right-criterion can be
established: Let k be an edge of the triangulation with the
endpoints A and B, with coordinate-vectors a and b. Let n be
the surface-normal in A, and P, coordinate-vector p, the point
to be inserted. P lies to the right of the edge k, if
d = ((kxn),(p—a) > 0 (figure 2).
A kxn
Fig. 2: Order-criterion using the surface-normal.
This order-criterion is repeatedly applied to the edges of the
triangulation, until the correct triangle is found.
The surface-normal in a data-point is estimated with the use of
the neighbours of the point. A common method is to build the
normals on every triangle the point belongs to. The normal in
the point results as a weighted sum of these triangle-normals.
Whenever the triangulation changes, all concerned normals
will be refined. Sometimes the normals are given a priori, in
that case these vectors will be used - e.g. in automatic image
matching the object-normals easily can be estimated.
Nevertheless, the estimated normals sometimes are only rough
approximations of the actual normals what may lead to errors
in the locating-step.
If additional information exists - such as break-lines or
contour-lines -, they will be utilized for the locating of the
triangle, as well as for the estimation of the normals. Finally, it
is planned to check the correctness of the integration with
regard to blunder detection.
3.3 Integration of the point
As soon as the correct triangle has been found, the point will
be inserted, i.e. all necessary edges are build. The point can
also lie outside the triangulated region. In that case the point
has to be connected with the „visible“ part of the boundary.
3.4 Optimization
As mentioned above, the topological relations between the
data-points are not uniquely determined. Nor is the triangula-
tion of the point-set. One has to formulate a criterion to de-
termine the result of the triangulation. Such criterions are
known as optimization-criterions, as the criterion optimizes the
triangulation in a specific sense.
Commonly, as in this work, the optimization-criterion is
applied edgewise (Cline, 1984 and Choi, 1988): an existing
edge of the triangulation will be tested, whether the criterion is
hurt or not. If. the edge doesn't match the criterion, it will be
swapped in the corresponding quadrilateral - see figure 3.
B
RU
SU
Fig. 3: Swapping of an edge.
The best-known optimizing-criterion is the circle-criterion,
which is equivalent to the max-min criterion. This criterion
leads to the well-known Delaunay-triangulation. This triangu-
lation is optimal in the sense that it produces regular triangles,
near to equilateral triangles. Unfortunately, these algorithms
are 2D only.
For our 3D-triangulation several criterions have been imple-
mented and tested:
' 3D-Delaunay' - the minimum angle of two adjacent tri-
angles is maximized.
‘Smoothness1' - the angle between the planes of two
adjacent triangles is maximized, thus to gain a smooth
surface.
'Smoothness2' - the minimum angle between the planes
of the two adjacent triangles and the four neighbour-
triangles is maximized. This method was presented in
Choi, 1988.
'Smoothness3' - a combination of Smoothnessl and
Smoothness2.
‘Greedy' - the sum of the length of the edges is
minimized. The greedy-triangulation is a widley used
method.
2D-Delaunay' - the triangulation is optimized by
applying the Delaunay-criterion to the ground-pro-
jection of the points. Naturally, all other 2D-criterions
could be used also. .
combinations - all above criterions can be combined by
a target function to form new criterions.
The optimization-criterions can be - or have to be - extended
with further constraints, e.g. conditions to avoid irregular
swaps, which would lead to overlapping triangles.
3.5 Constraints
For a flexible modelling of surfaces, it should be possible to
apply topological constraints on the triangulation. A prominent
example are lines, which are included as a chain of edges.
These edges must exist within the triangulation. In the last step
of the insertion of a point such constraints are introduced.
Figure 4 shows an example for a constraint-edge. The building
of this edge works again with the use of the local order-
criterion.
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International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B4. Vienna 1996