| XXXIX-B3, 2012
iD PHOTO-
LET PCS
pei 10610, Taiwan -
ct Georeferencing,
from pictures taken by
en the bottleneck of 3D
TEMS), camera, global
These sensors bring the
of these sensors cannot
rs are not capable of
n to iteratively improve
ire treated as the initial
age exterior orientation
vireframe model of the
n the picture.
juares adjustments is
entation.
3D building models
delling the object; (2)
) creating the realistic
, the aerial photographs
: models of buildings,
al computing device is
ig the “Floating Model”
ge orientation problem
the semi-automated
s Model-image fitting
; inter-acting interface
choose suitable model,
the model so it can
n ad-hoc Least-squares
veloped to solve the
del line segments and
model can be extracted
mined, the creation of
alled inverse mapping.
insforming and image
«flow of the proposed
rocedures.
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
Precisely | Geometric
Fitting (LSMIF) 7 Models
t d 4 /
AARAU és
»/ Photo-realistic3D |
A Building Models
E S ERR UE UU pr v < es
| GPS & | rrr T UK E
Selection | £ G-Sensors ——» Projecton | Projection |
Le id A Parameters | / E ; Ë ee
ER at) elm er
[ [A Closerange | |^ — | f prede y BE 8 A
| Model Base | | Photograph | Precisely | ,/ / ioral Facade
| |} Pn — Image —» Image Clipping —
ITEM ed ee CSMIF} / Orientation / | Texture
Figure 1: The proposed photo-realistic 3D building modelling procedure
In the proposed workflow, there are still two procedures -
“model selection" and "approximately fitting" requires human
interactions. This is because manual image interpretation is
more robust and more efficient than computer algorithms.
While the other computational work, such as “model
projection", "precisely fitting", and "image clipping", are
carried out by computer algorithms. Therefore, the proposed
procedure shall improve the efficiency from the full-manual
methods, while remain robust than full-automated approaches.
2. MODEL-IMAGE CORRESPONDENCE
To deal with the modelling problem, this paper adopted the
concept of floating models (Wang, 2004). The floating models
can be categorized into four types: point, linear feature, plane,
or volumetric solid. Each type contains various primitive
models for the practical needs. For example, the linear feature
includes the line segment and the arc. The plane includes the
rectangle, the circle, the ellipse, the triangle, the pentagon, etc.
The volumetric solid includes the box, the gable-roof house, the
cylinder, the cone, etc. Despite the variety in their shape, each
primitive model commonly has a datum point, and is associated
with a set of pose parameters and a set of shape parameters. The
datum point and the pose parameter determine the position of
the floating model in object space. It is adequate to use 3
translation parameters (dX, dY, dZ) to represent the position
and 3 rotation parameters, tilt (f) around Y-axis, swing (s)
around X-axis, and azimuth (a) around Z-axis to represent the
rotation of a primitive model. Figure 2 shows four examples
from each type of models with the change of the pose
parameters. X"-Y'-Z' coordinate system defines the model
space and X-Y-Z coordinate system defines the object space.
The little pink sphere indicates the datum point of the model.
The yellow primitive model is in the original position and pose,
while the grey model depicts the position and pose after
changing pose parameters (dX, dY, dZ, t, s, a). The model is
"floating" in the space by controlling these pose parameters.
The volume and shape of the model remain the same while the
pose parameters change. The shape parameters describe the
shape and size of the primitive model, e.g., a box has three
shape parameters: width (w), length (/), and height (A).
Changing the values of shape parameters elongates the
primitive in the three dimensions, but still keeps its shape as a
rectangular box. Various primitive may be associated with
different shape parameters, e.g., a gable-roof house primitive
has an additional shape parameter — roof’s height (rk). Figure 3
shows three examples from each type of models with the
change of shape parameters. The point is an exceptional case
that does not have any shape parameters. The yellow one is the
original model, while the grey one is the model after changing
the shape parameters. The figure points out the other important
Characteristic of the floating model — the flexible shape with
Certain constraints. Changing the shape parameters does not
affect the position or the pose of the model.
i 2
zt :
Y
quA X
Y\
hz °F
dX
Rectangle Plane Box Solid
Figure 2: Pose parameters adjustment of floating models
3 I:
1 i
LUNA CURE AU NAGER AU AU AUS
Line Segment | Rectangle Plane Box Solid
Figure 3: Shape parameters adjustment of floating models
When the pictures are taken, buildings are projected on the
picture based on the central projection. The object point,
exposing centre, and the image point should lie on the same
straight line, which is the essential of the collinearity equations.
If the object point is expanded to a volumetric solid, there
would be unlimited rays along the boundary. When re-project a
floating model onto the taken photo, all of the model
parameters and image orientation parameters must be accurate
so the wireframe model can perfectly superimpose on the
building's image. Figure 4 shows the incorrect model
projection either based on the incorrect model parameters or
based on the incorrect image orientation parameters.
Yos 0.4.
0,(X,;,Y,, nr; ‚6; ‚KK »
(a) Projection based on incorrect image orientation parameters
