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Ta b l e 9 . 2
Example 2: upper and lower bounds of the worst-case location errors for the object
points in Figure 9.2
δ
s
r
(δ)
s
r
(δ)
s
t
(δ)
s
t
(δ)
[pixels] [deg]
[deg]
[mm] [mm]
0
.
5
0
.
141 0
.
703 0
.
185 0
.
789
1
.
0
0
.
473 1
.
405 0
.
996 1
.
577
1
.
5
1
.
089 2
.
108 1
.
492 2
.
367
2
.
0
1
.
895 2
.
812 1
.
982 3
.
158
9.4.2
Example 2
Here we consider the situation shown in Figure 9.2. Again, the chosen object points
are the centers of the ten large dots. The screen size and the camera intrinsic param-
eters are as in Example 1. Table 9.2 shows the upper bounds
s
r
(
) and
s
t
(
δ
δ
) in
(9.24)-(9.25) and the lower bounds
s
r
(
) and
s
t
(
δ
δ
) in (9.27) for some values of
δ
.
9.4.3
Example 3
Let us consider the real image shown in Figure 9.3 where twelve object points are
observed. The 3D points have been estimated by acquiring a second image from
another location, and then performing a standard 3D reconstruction of the object
(the camera pose has been estimated through the essential matrix with an estimate
Fig. 9.3
Example 3: real image with twelve observed points
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