Boulanger, Pierre
To prepare the various models used in this system a modeling workstation combining various in-house and commercial
software was developed. Realax Corporation developed the scene graph editor RxScene used in this project. This editor
allows for easy graphic style editing of the scene graph and is truly compatible with the Performer library. In the next
section, we will describe the various phases used to prepare the VR mine model.
2.1.1 Terrain Modeling
The mine terrain model was created from differential GPS survey data supplied by Syncrude. The precision of the data
set was in the order of 20 cm. This is quite good considering the fact that the mine covers an area of approximately 5-
km by 5 km. As one can see in Figure 2b, these data come in a relatively sparse form, usually because surveyors follow
roads or the edge of a cliff. To transform the sparse data into a useful terrain model, we created a triangle mesh
approximating the measured data. In order to do so, we used a 3D Delaunay triangulation algorithm [Edelsbrunner,
1998] implemented in a commercial software called WRAP supplied by Geomagic Inc. The software produced very
good results and the resulting terrain model required minimal post-processing.
The second phase of the modeling project was to register a LANDSAT satellite picture against the terrain model (see
Figure 2c). Using the road structures as our guide and a projective texture mapping software developed in-house, we
were able to manually locate the correspondence between the terrain model and the texture. One can see in Figure 2b
the resulting terrain model combining the satellite texture and the survey data. We also experimented with various
automated registration algorithms [Weinhaus, 1997] but most of them did not produce results as good as the manual
technique. The main reason is that it is hard to detect the same structures between the terrain model and the picture.
The third phase of the terrain modeling process was to add the ore concentration as an overlay. In most mining
operations a series of regularly spaced drillings are performed in a rectangular manner over the region to be excavated.
The drillings positions are determined using a differential GPS (DGPS) system in a central mine coordinate system.
Each drilling core is then analyzed for bitumen concentration as a function of depth. The resulting data set is a
volumetric map of ore concentration. In order to create a color map of the ore concentration for a given terrain
condition, a color texture was generated and overlaid over the terrain model. Since each ore concentration datum is not
really on a regular volume, an interpolation algorithm was implemented to estimate the ore concentration over a regular
volume of size 20 m x 20 m x 20 m. From the resulting structure one can then slice the volume of data to any depth and
produce a high-density texture map used to create the overlays. The slicing surface is the terrain model at its current
depth. An update of the texture can be performed as new estimates of the terrain shape are computed. One can see in
Figure 2a the various layers of the ore data and in F igure 2b the texture map over the terrain model.
Figure 2: Model creation process for the north mine model.
(a) Ore concentration data, (b) Final model with survey data overlaid, and (c) LANDSTAT picture of the
region
The last part of the modeling technique consists on optimizing the geometry for VR viewing. Techniques such as
dividing the terrain model in smaller sections to optimize the culling process and the transformation of the LANDSAT
texture into Clip Texture to minimize the usage of texture memory were used.
2.1.2 Infrastructure Modeling
94 International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B5. Amsterdam 2000.
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