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pictures taken from different locations. It is beyond the scope of this paper to describe photogrammetric methods in 
detail. One can refer to the large body of work in this field to get more detailed information [Brown,1976] 
[ElHakim, 1997]. 
Before any measurement is performed, one must first calibrate the camera to determine all the internal calibration 
parameters such as pixel size, lens distortions, etc. Once the camera is calibrated, we need to be able to determine from 
a common point in the image, the orientation of the camera and the 3D position of the points selected. If some of these 
3D points correspond to the footprint of the building as measured by the DPGS, a rigid transformation between these 
points is computed and applied to the rest of the measurements. The resulting data set is in the central coordinate system 
of the mine and can be easily integrated with the terrain model. 
The last phase of the model building process consists of using these measurements to create a series of textured 
polygons representing the main features of each building. The textures are extracted from the pictures by using a back 
projection algorithm [El-hakim, 1998]. This is the lengthiest part of the modeling process. If one wants to model a 
building with a large amount of detail, one has to spend a long time extracting the measurements for each of these 
features. In this project, we used an in-house software called ShapeCapture. In Figure 3, on can see a 3D-textured model 
of the NRC M50 building created by ShapeCapture software. 
  
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Figure 3: 3D textured model of NRC building created by ShapeCapture. 
2.1.3 Modeling Equipment 
So far, we only dealt with the static part of the model. However, we also need to model the equipment. Contrary to the 
static part of the model such as the terrain or the infrastructure which do not have any dynamic section, the equipment 
models must have moving sections that need to be actuated. 
One technique to model such systems is to start from a drawing and use an advanced modeling software such as 3D 
Studio to build a geometric representation of the equipment, i.e., model separately, every moving parts. Once each 
moving part of the equipment is built, we can then connect them topologically by using a scene graph technique. One 
can see in Figure 4 the 3D model of the Hitachi EX200 excavator used in these experiments and in Figure 5 a section of 
the scene graph representing the model. 
A complete kinematics model of the excavator has been developed, allowing a fully articulated model that can be 
controlled and animated by data coming from either a control device (a joystick here) or from sensor data measured 
from the real excavator (joints positions sensors in this case). The animation is performed by associating to each moving 
joint a dynamic coordinate system that is connected virtually to a sensor. Using this technique, we had to create many 
new scene graph nodes to accommodate all sorts of new functions. Using this technique one can replace the texture of a 
polygon by video images coming from an active video camera called REMCAM located on the network, or change the 
color of a hydraulic actuator as a function of its pressure. In fact, one can map any sensor to any property defined in the 
  
International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B5. Amsterdam 2000. 95