me XXXIX-B3, 2012 
à DATA AND 
N, 
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versity, 
[odelling 
ch cannot be detected by 
ion, monitoring electrical 
quire the 3D coordinates 
borne laser scanner data, 
hapes or fitted geometric 
oint clouds are obtained. 
mera is equipped with an 
pes using airborne laser 
images by simultaneous 
borne laser scanner data. 
. visualization of normal 
' coordinates of multiple 
cteristic image quantities 
f the 2D coordinates of 
g object shapes for 3D 
quire digital images if a 
\LS system. The digital 
s camera calibration for 
nts. When a non-metric 
ientation parameters are 
| test sheet or test target. 
ited in severe conditions 
ires, camera calibration 
‘he authors have been 
3D measurement system 
, consumer-grade digital 
d Measurement (IBIM) 
"m, which uses digital 
ice meter (Nakano and 
rameters of the triplet 
'CPs are simultaneously 
distance condition, and 
ssible to integrate point 
he concept of the IBIM 
tion. With this motive, 
le adjustments with self- 
aper so that exterior 
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B3, 2012 
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia 
orientation parameters obtained from the GNSS/IMU system, 
distances and 3D object coordinates acquired from the laser 
scanner, and the interior orientation parameters are 
simultaneously ^ adjusted. Combined block adjustment 
orientations were proposed in the late 1900's (Ackermann et al., 
1972, EL-Hakim & Faig, 1981, Chikatsu et al, 1988). The 
proposed adjustment is widely expected to enable the utilization 
of the airborne laser scanner in generating large-scale maps and 
efficient aerial photogrammetry should be accomplished, except 
for geodetic data such as ground control points and aerial 
triangulation. Therefore, this paper uses calibration of non- 
metric digital cameras to integrate point clouds and digital 
images. 
The object extraction procedures using ALS data and digital 
images are performed in three steps. 
1) A rough 3D object shape is extracted using a normal vector 
map that is created from TIN by point clouds. Visualization of 
normal vectors is useful for operator interpretation. 
2) The rough object shapes are converted into multiple image 
coordinates by a collinearity condition. The 2D shape 
coordinates of detailed images are acquired using image 
characteristics from around the rough shape. 
3) The detailed 3D shape is computed using the spatial 
intersection of detailed 2D shape coordinates and orientation 
parameters. 
A flowchart of the object extraction procedure is shown in 
Figure 1. 
Distances Exterior Interior Images 
Orientation Orientation 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
wig Image 
: Coord. 
Point 
clouds 
^ 
Normal vector : Camera 
map calibration 
Rough shape : ..| Rough shape 
(30) ? (2D) 
wis 
Y 
Edge t 
  
  
extraction (2D) 
  
^ d 
  
Detailed shape 
(3D) 
  
  
  
Figure 1. Object extraction flowchart 
2. CAMERA CALIBRATION 
The authors have been concentrating on developing a close 
range measurement system for consumer grade digital cameras 
using triplet images (Chikatsu et al., 2006). The measurement 
system was adopted into digital aerial photogrammetry in this 
paper because triplet images have following characteristics. 
- Triplet images have advantages in generating stereo pairs. 
- Triplet images have the flexibility for multiple images. 
- Triplet images have the ability to increase geometric 
restriction. 
Moreover, the IBIM system of the basic camera calibration 
concept has distance condition characteristics and also uses 
pseudo ground control points (GCPs), which are virtual points. 
Figure 2 shows the measurement concept used in this paper. 
On the other hand, lens distortion is the most important interior 
orientation parameter, and many distortion models have been 
proposed (Brown, 1971, Murai, Matsuoka, Okuda, 1984). This 
paper uses Brown's 1971 model, which takes the 7th degree of 
the radial polynomial equation and the tangential distortion into 
account, and has been widely used in close range 
photogrammetric fields. 
seus er +K,r’ - Kr) B(? +2x s 2Px'y 
r 
Y (kp Kr eR )e20xy B 25?) (1) 
y=y at 
where = = x"? + y’! = the radial distance from the principal 
points 
x, y = corrected image coordinates 
x', y'= image coordinates 
Ki, K,, K3 = radial distortion coefficients 
P,, P,= tangential distortion coefficients 
Flight direction A 
ere tr es E es +9000 epe 
  
  
      
   
  
: Perspective center 
:Irradiation point of laser 
:Point clouds 
Figure 2. Measurement concept 
The exterior parameters (Xo, Yo, Zo, c», p, K) and the interior 
parameters (/ [focal length], wo, vo [principal points], a, b [scale 
factor, shear factor], Ki, Ko, K;, Pi, P, [lens distortion]) are 
unknown parameters of the multiple images and the pseudo- 
GCPs (X; Y,, Z;), respectively. These unknown parameters are 
simultaneously calculated by the collinearity condition, distance 
condition, and geometric constraint condition under the local 
coordinate system. Here, the collinearity condition is shown as 
Equation (2) and the distance condition is shown as Equation 
(3). 
  
  
x zy Pa(X 7 X4) ma (f - Y) ms (Z - Z,) 2 
m,,(X — À, m (Ye Tm, Z -Z,) Q) 
y=f 2 - A, +m,,(Y —Y, + M, Z-Z,) 
my (X - X,)* my (Y -Y,)* m5(Z - Z,) 
where x, y 7 corrected image coordinates 
f= focal length 
X, Y, Z = pseudo-GCP object coordinates 
Xo, Yo, Zo = perspective center 
my, = rotation matrix elements