Abstract
Architectural styles are phases of development that classify architecture in the sense of historic periods, regions and cultural influences. The article presents the first approach, performing automatic segmentation of building facade towers in the framework of an image-based architectural style classification system. The observed buildings, featuring towers, belong to Romanesque, Gothic and Baroque architectural styles. The method is a pipeline unifying bilateral symmetry detection, graph-based segmentation approaches and image analysis and processing technique. It employs the specific visual features of the outstanding architectural element tower - vertical bilateral symmetry, raising out of the main building and solidity. The approach is robust to high perspective distortions. It comprises two branches, targeting facades with single and double towers correspondingly. The performance evaluation on a vast number of images reports extremely high segmentation precision.
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Google Visual Search Engine http://images.google.com.
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Note that the rows in an image count down from the upper row, so the minimum row is the highest and the maximum - the lowest.
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Shalunts, G. (2015). Segmentation of Building Facade Towers. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2015. Lecture Notes in Computer Science(), vol 9475. Springer, Cham. https://doi.org/10.1007/978-3-319-27863-6_17
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DOI: https://doi.org/10.1007/978-3-319-27863-6_17
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