A Bayesian Estimation of Building Shape Using MCMC

dc.contributor.authorDick, A.
dc.contributor.authorDyer, F.
dc.contributor.authorCipolla, R.
dc.contributor.conferenceEuropean Conference on Computer Vision (7th : 2002 : Copehagen, Denmark)
dc.contributor.editorHeyden, A.
dc.contributor.editorSparr, G.
dc.contributor.editorNielsen, M.
dc.contributor.editorJohansen, P.
dc.date.issued2002
dc.descriptionThe original publication can be found at www.springerlink.com
dc.description.abstractThis Paper investigates the use of an implicit Prior in Bayesian model-based 3D reconstruction of architecture from image sequences. In our previous work architecture is represented as a combination of basic primitives such as windows and doors etc, each with their own Prior. The contribution of this work is to provide a global Prior for the spatial organization of the basic primitives. However, it is difficult to explicitly formulate the Prior on spatial organization. Instead we define an implicit representation that favours global regularities prevalent in architecture (e.g. windows lie in rows etc.). Specifying exact Parameter values for this Prior is problematic at best, however it is demonstrated that for a broad range of values the Prior provides reasonable results. The validity of the Prior is tested visually by generating synthetic buildings as draws from the Prior simulated using MCMC. The result is a fully Bayesian method for structure from motion in the domain of architecture
dc.description.statementofresponsibilityA.R. Dick, P.H.S. Torr and R. Cipolla
dc.identifier.citationComputer Vision - ECCV 2002: 7th European Conference on Computer Vision; 2002/ A. Heyden, G. Sparr, M. Nielsen, P. Johansen (eds.): pp. 852−866
dc.identifier.doi10.1007/3-540-47967-8_57
dc.identifier.isbn3540437444
dc.identifier.isbn9783540437444
dc.identifier.issn0302-9743
dc.identifier.issn1611-3349
dc.identifier.orcidDick, A. [0000-0001-9049-7345]
dc.identifier.urihttp://hdl.handle.net/2440/33971
dc.language.isoen
dc.publisherSpringer-Verlag
dc.publisher.placeLondon, UK
dc.relation.ispartofseriesLecture notes in computer science ; 2351
dc.source.urihttp://www.springerlink.com/content/ntcw8g5e2yj27398/?p=b00274028002458f8f5422d7436f31e9&pi=7
dc.titleA Bayesian Estimation of Building Shape Using MCMC
dc.typeConference paper
pubs.publication-statusPublished

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