TY - GEN
T1 - Quasi-regular facade structure extraction
AU - Han, Tian
AU - Liu, Chun
AU - Tai, Chiew Lan
AU - Quan, Long
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84875875765&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84875875765&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-37447-0_42
DO - 10.1007/978-3-642-37447-0_42
M3 - Conference contribution
AN - SCOPUS:84875875765
SN - 9783642374463
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 552
EP - 564
BT - Computer Vision, ACCV 2012 - 11th Asian Conference on Computer Vision, Revised Selected Papers
T2 - 11th Asian Conference on Computer Vision, ACCV 2012
Y2 - 5 November 2012 through 9 November 2012
ER -