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.
CITATION STYLE
Koziński, M., Obozinski, G., & Marlet, R. (2015). Beyond procedural facade parsing: Bidirectional alignment via linear programming. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9006, pp. 79–94). Springer Verlag. https://doi.org/10.1007/978-3-319-16817-3_6
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