Full text: Proceedings, XXth congress (Part 3)

International Archives of the Photogrammetry, Remote Sensing 
e Guidelines for a matching algorithm. For some appli- 
cations, we can suppose that the reliability of the viewing 
parameters and the 3D reconstruction is fixed. Hence, our 
bundle adjustment algorithm with error propagation can as- 
sess when the reliability goal is reached. If not, the match- 
ing algorithm still has to extract and match more features in 
order to increase the reliability in the given parameters. 
e Dealing with large scale surveys. The experiments were 
performed with a reduced amount of data (20-30 images, 
several hundreds of measures). Dealing with large-scale 
surveys will necessitate an optimized design and we will 
have to handle sparse matrix. Some optimization processes 
are well known in the photogrammetric community and de- 
scribed in (Triggs et al., 2000). 
e Spatial reasoning. A very promising area of research con- 
cerns the way to choose points and lines in images in order 
to improve the accuracy of the estimated parameters. As a 
matter of fact, the spatial distribution of the features (points 
and lines) inside the images, as well as the geometric ar- 
rangement of the camera, have a tremendous impact on the 
accuracy of the estimation of the different parameters of a 
bundle adjustment problem (Michaelsen and Stilla, 2003). 
Correlation analysis between different parameters will be of 
interest in order to estimate the crucial parameters. 
Introducing more knowledge concerning the data. More 
constraints or parameters can be introduced depending on 
the knowledge we have of the scene. For instance, vertical 
lines can be introduced in the bundle adjustment thanks to 
vanishing points or constraints on the 3D lines (Bentrah et 
al.. 2004), (Van den Heuvel, 2001). 
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* Institut 
^ INRIA Rhóne- 
KEY WORDS: 
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