This paper proposes an automated method to detect, group and rectify arbitrarily- arranged coplanar repeated elements via energy minimization. The proposed energy functional combines several features that model how planes with coplanar repeats are projected into images and captures global interactions between different coplanar re- peat groups and scene planes. An inference framework based on a recent variant of α-expansion is described and fast convergence is demonstrated. We compare the pro- posed method to two widely-used geometric multi-model fitting methods using a new dataset of annotated images containing multiple scene planes with coplanar repeats in varied arrangements. The evaluation shows a significant improvement in the accuracy of rectifications computed from coplanar repeats detected with the proposed method versus those detected with the baseline methods.

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