In: Stilla U, Rottensteiner F, Paparoditis N (Eds) CMRT09. IAPRS, Vol. XXXVIII, Part 3A/V4 — Paris, France, 3-4 September, 2009
depends on its resolution and varies with the distance from the
camera to the facade.
Another possible evolution is to use additional 3D information
to predict occlusions. A Digital Terrain Model could be used to
predict hidden parts due to hills or embankments (case of a hill
masking buildings facades located on the other side of a square
for instance). If available, a complete 3D city model including
vegetation and detailed building roofs would help better
estimate the visibility of a given façade. More generally, an
environment mask as in described in (Wang et al., 2002) could
be introduced.
Another parameter to take into account is the uncertainty on the
GPS/IMU data which introduces an uncertainty on the camera
position and direction. In order to guarantee a complete
selection, a simple solution would be to dilate each wall
polygon by the maximal distance induced by the positioning
uncertainty. In a similar way, the influence of the input 3D
model accuracy should be investigated.
For this particular study, only synthetic data have been used. In
the future we will be working on real data, and the influence of
both the positioning error and the 3D model accuracy will be
studied. Figure 9 gives an idea of what we would like to
automatically achieve at a large scale. Note that the side facade
located at the top right of the image cannot be textured if the
image selection process is only 2D-based.
Glassner, A., 1984. Space subdivision for fast ray tracing.
IEEECG&A, 4( 10): 15-22, Oct. 1984.
Goulette, F., Nashashibi, F., Abuhadrous, I., Ammoun, S. and
Laurgeau, C., 2007. An Integrated On-board Laser Range
Sensing System for On-the-way City and Road Modelling. In
ISPRS Comm. I Symposium, Marne-la-Vallée, France, 2004.
Greene, N., Kasse, M., Miller, G., 1993. Hierarchical Z-buffer
visibility. In Proc. Of the 20 th conf. On Computer graphics and
interactive techniques, Anaheim, CA, 1993.
Haala, N., 2004. On the refinement of urban models by
terrestrial data collection. In XXth ISPRS Congress, Vol. 35,
Part B, Istanbul, Turkey, 2004.
Hunter, G, 2009. Streetmapper mobile mapping system and
applications in urban environments. In ASPRS Annual
Conference, Baltimore, USA, 2009
Jevans, D. and Wyvill, B. Adaptive voxel subdivision for ray
tracing. Proc. Graphics Interface '89,164-172, June 1989.
Mrstik, P., and Kusevic, K., 2009. Real Time 3D Fusion of
Imagery and Mobile Lidar, ASPRS Annual Conference,
Baltimore, USA, 2009.
Pénard, L., Paparoditis, N. and Pierrot-Deseilligny, M., 2005.
3D Building Facade Reconstruction under Mesh Form from
Multiple Wide Angle Views, In IAPRS vol. 36 (Part 5/WI7),
2005.
Strasser, W. Schnelle kun>en und Flächendarstellung auf
graphishen Sichtgeräten, Ph.D. Thesis D83, Technical
University of Berlin, Germany, 1974
Figure 9 - 3D virtual view of the historical centre of Rennes
REFERENCES
Aliène, C., Pons, J.P. and Keriven R., 2008. Seamless image-
based texture atlases using multi-band blending. Pattern
Recognition, ICPR 2008.
Bentrah, 0., Paparoditis, N., Pierrot-Deseilligny, M., 2004.
Stereopolis : An Image Based Urban Environments Modelling
System. In International Symposium on Mobile Mapping
Technology (MMT), Kunming, China, March 2004.
Brun, X., Deschaud, J.E. and Goulette, F., 2007, On-the-way
City Mobile Mapping Using Laser Range Scanner and Fisheye
Camera, In International Symposium on Mobile Mapping
Technology (MMT), Padua, Italy2007.
