Abstract
We propose a novel formulation for parsing facade images with user-defined shape prior. Contrary to other state-of-the-art methods, we do not explore the procedural space of shapes derived from a grammar. Instead we formulate parsing as a linear binary program which we solve using Dual Decomposition. The algorithm produces plausible approximations of globally optimal segmentations without grammar sampling. It yields state-of-the-art performance on standard datasets.
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Acknowledgements
This work was carried out in IMAGINE, a joint research project between Ecole des Ponts ParisTech (ENPC) and the Scientific and Technical Centre for Building (CSTB). It was partly supported by ANR project Semapolis ANR-13-CORD-0003.
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Koziński, M., Obozinski, G., Marlet, R. (2015). Beyond Procedural Facade Parsing: Bidirectional Alignment via Linear Programming. In: Cremers, D., Reid, I., Saito, H., Yang, MH. (eds) Computer Vision -- ACCV 2014. ACCV 2014. Lecture Notes in Computer Science(), vol 9006. Springer, Cham. https://doi.org/10.1007/978-3-319-16817-3_6
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