D. Ceylan, N.J. Mitra, Y. Zheng, M. Pauly
ACM Transactions on Graphics, volume 33, issue 1, article 2, (2014)
Repeated structures are ubiquitous in urban facades. Such repetitions lead
to ambiguity in establishing correspondences across sets of unordered images. A decoupled structure-from-motion
reconstruction followed by symmetry detection often produces errors: outputs are either noisy and incomplete, or
even worse, appear to be valid but actually have a wrong number of repeated elements. We present an optimization
framework for extracting repeated elements in images of urban facades, while simultaneously calibrating the input
images and recovering the 3D scene geometry using a graph-based global analysis. We evaluate the robustness of
the proposed scheme on a range of challenging examples containing widespread repetitions and non-distinctive features.
These image sets are common but cannot be handled well with state-of-the-art methods. We show that the recovered
symmetry information along with the 3D geometry enables a range of novel image editing operations that maintain
consistency across the images.