Image-based procedural modeling of facades
ACM SIGGRAPH 2007 papers
A stochastic grammar of images
Foundations and Trends® in Computer Graphics and Vision
Discovering structural regularity in 3D geometry
ACM SIGGRAPH 2008 papers
3D modeling of haussmannian facades
MIRAGE'11 Proceedings of the 5th international conference on Computer vision/computer graphics collaboration techniques
Quasi-regular facade structure extraction
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part IV
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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.