MODELLING AND INTERPRETATION OF ARCHITECTURE FROM SEVERAL IMAGES
A. R. Dick, P. H. S. Torr, R. Cipolla
2003
A. R. Dick, P. H. S. Torr, R. Cipolla
This paper describes the automatic acquisition of three dimensional architectural models from short image sequences. The approach is Bayesian and model based. Bayesian methods necessitate the formulation of a prior distribution; however designing a generative model for buildings is a difficult task. In order to overcome this a building is described as a set of walls together with a `Lego' kit of parameterised primitives, such as doors or windows. A prior on wall layout, and a prior on the parameters of each primitive can then be defined. Part of this prior is learnt from training data and part comes from expert architects. The validity of the prior is tested by generating example buildings using {\sc MCMC} and verifying that plausible buildings are generated under varying conditions. The same {\sc MCMC} machinery can also be used for optimising the structure recovery, this time generating a range of possible solutions from the posterior. The fact that a range of solutions can be presented allows the user to select the best when the structure recovery is ambiguous.
If you have difficulty viewing files that end '.gz',
which are gzip compressed, then you may be able to find
tools to uncompress them at the gzip
web site.
If you have difficulty viewing files that are in PostScript, (ending
'.ps' or '.ps.gz'), then you may be able to
find tools to view them at
the gsview
web site.
We have attempted to provide automatically generated PDF copies of documents for which only PostScript versions have previously been available. These are clearly marked in the database - due to the nature of the automatic conversion process, they are likely to be badly aliased when viewed at default resolution on screen by acroread.