Abstract
This paper presents a syntactic model for architectural floor plan interpretation. A stochastic image grammar over an And-Or graph is inferred to represent the hierarchical, structural and semantic relations between elements of all possible floor plans. This grammar is augmented with three different probabilistic models, learnt from a training set, to account the frequency of that relations. Then, a Bottom-Up/Top-Down parser with a pruning strategy has been used for floor plan recognition. For a given input, the parser generates the most probable parse graph for that document. This graph not only contains the structural and semantic relations of its elements, but also its hierarchical composition, that allows to interpret the floor plan at different levels of abstraction.
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© 2011 Springer-Verlag Berlin Heidelberg
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de las Heras, LP., Sánchez, G. (2011). And-Or Graph Grammar for Architectural Floor Plan Representation, Learning and Recognition. A Semantic, Structural and Hierarchical Model. In: Vitrià, J., Sanches, J.M., Hernández, M. (eds) Pattern Recognition and Image Analysis. IbPRIA 2011. Lecture Notes in Computer Science, vol 6669. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21257-4_3
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DOI: https://doi.org/10.1007/978-3-642-21257-4_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21256-7
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