In this paper we present a novel two-stage framework for extracting what we define as a quasi-regular structure in facade images. A quasi-regular structure is an irregular rectangular grid representing the placements of repetitive structural architecture objects, e.g., windows, in a facade. Such a structure generalizes a perfect lattice structure generated by the 2D symmetry groups, studied by the previous work. First, we propose to formulate the quasi-regular structure detection in an object-oriented Marked Point Process framework by treating the architectural elements as objects. This leads to an initial quasi-regular structure map which serves as an indicator map of potential object locations. Then, we propose a regularization scheme to recover the complete quasi-regular structures from the initial incomplete structure. This stage takes advantage of the intrinsic low rank constraint of the quasi-regular structure representing a regularized facade. By applying such a regularization, the complete quasi-regular facade structure is obtained. We have extensively tested our method on a large variety of facade images, and demonstrated both the effectiveness and the robustness of our two-stage framework. © 2013 Springer-Verlag.
CITATION STYLE
Han, T., Liu, C., Tai, C. L., & Quan, L. (2013). Quasi-regular facade structure extraction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7727 LNCS, pp. 552–564). https://doi.org/10.1007/978-3-642-37447-0_42
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