cvpr cvpr2013 cvpr2013-228 cvpr2013-228-reference knowledge-graph by maker-knowledge-mining
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Author: Julien Weissenberg, Hayko Riemenschneider, Mukta Prasad, Luc Van_Gool
Abstract: Urban models are key to navigation, architecture and entertainment. Apart from visualizing fa ¸cades, a number of tedious tasks remain largely manual (e.g. compression, generating new fac ¸ade designs and structurally comparing fa c¸ades for classification, retrieval and clustering). We propose a novel procedural modelling method to automatically learn a grammar from a set of fa c¸ades, generate new fa ¸cade instances and compare fa ¸cades. To deal with the difficulty of grammatical inference, we reformulate the problem. Instead of inferring a compromising, onesize-fits-all, single grammar for all tasks, we infer a model whose successive refinements are production rules tailored for each task. We demonstrate our automatic rule inference on datasets of two different architectural styles. Our method supercedes manual expert work and cuts the time required to build a procedural model of a fa ¸cade from several days to a few milliseconds.
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