Abstract
We propose a novel method for recognition of structured images and demonstrate it on detection of windows in facade images. Given an ability to obtain local low-level data evidence on primitive elements of a structure (like window in a facade image), we determine their most probable number, attribute values (location, size) and neighborhood relation. The embedded structure is weakly modeled by pair-wise attribute constraints, which allow structure and attribute constraints to mutually support each other. We use a very general framework of reversible jump MCMC, which allows simple implementation of a specific structure model and plug-in of almost arbitrary element classifiers. The MC controls the classifier by prescribing it “where to look”, without wasting too much time on unpromising locations.
We have chosen the domain of window recognition in facade images to demonstrate that the result is an efficient algorithm achieving performance of other strongly informed methods for regular structures like grids, while our general model covers loosely regular configurations as well.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Micusik, B., Kosecka, J.: Piecewise planar city 3D modeling from street view panoramic sequences. In: Proc. CVPR (2009)
Hohmann, B., Krispel, U., Havemann, S., Fellner, D.: CITYFIT: High-quality urban reconstructions by fitting shape grammars to images and derived textured point cloud. In: Proc. of the International Workshop 3D-ARCH (2009)
Pauly, M., Mitra, N., Wallner, J., Pottmann, H., Guibas, L.: Discovering structural regularity in 3D geometry. Transactions on Graphics 27, 43 (2008)
Gips, J.: Shape grammars and their uses. Birkhäuser, Basel (1975)
Zhu, S., Mumford, D.: A stochastic grammar of images. Foundations and Trends in Computer Graphics and Vision 2, 362 (2006)
Alegre, F., Dellaert, F.: A probabilistic approach to the semantic interpretation of building facades. In: International Workshop on Vision Techniques Applied to the Rehabilitation of City Centres (2004)
Müller, P., Zeng, G., Wonka, P., Van Gool, L.: Image-based procedural modeling of facades. Transactions on Graphics 26, 85 (2007)
Mayer, H., Reznik, S.: Building facade interpretation from uncalibrated wide-baseline image sequences. ISPRS Journal of Photogrammetry and Remote Sensing 61, 371–380 (2007)
Ripperda, N., Brenner, C.: Data driven rule proposal for grammar based facade reconstruction. Photogrammetric Image Analysis 36, 1–6 (2007)
Teboul, O., Simon, L., Koutsourakis, P., Paragios, N.: Segmentation of building facades using procedural shape prior. In: Proc. CVPR (2010)
Toussaint, G.T.: The relative neighbourhood graph of a finite planar set. Pattern Recognition 12, 261–268 (1980)
McLaughlan, G.J.: Finite Mixture Models. Wiley, Chichester (2000)
Green, P.J.: Reversible jump Markov chain Monte Carlo computation and Bayesian model determination. Biometrika 82, 711–732 (1995)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Tyleček, R., Šára, R. (2011). A Weak Structure Model for Regular Pattern Recognition Applied to Facade Images. In: Kimmel, R., Klette, R., Sugimoto, A. (eds) Computer Vision – ACCV 2010. ACCV 2010. Lecture Notes in Computer Science, vol 6492. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19315-6_35
Download citation
DOI: https://doi.org/10.1007/978-3-642-19315-6_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-19314-9
Online ISBN: 978-3-642-19315-6
eBook Packages: Computer ScienceComputer Science (R0)