Automatic Constraint Detection for 2D Layout Regularization

Haiyong Jiang, Liangliang Nan, Dongming Yan, Weiming Dong, Xiaopeng Zhang, Peter Wonka

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


In this paper, we address the problem of constraint detection for layout regularization. As layout we consider a set of two-dimensional elements where each element is represented by its bounding box. Layout regularization is important for digitizing plans or images, such as floor plans and facade images, and for the improvement of user created contents, such as architectural drawings and slide layouts. To regularize a layout, we aim to improve the input by detecting and subsequently enforcing alignment, size, and distance constraints between layout elements. Similar to previous work, we formulate the layout regularization as a quadratic programming problem. In addition, we propose a novel optimization algorithm to automatically detect constraints. In our results, we evaluate the proposed framework on a variety of input layouts from different applications, which demonstrates our method has superior performance to the state of the art.
Original languageEnglish (US)
Pages (from-to)1933-1944
Number of pages12
JournalIEEE Transactions on Visualization and Computer Graphics
Issue number8
StatePublished - Sep 18 2015

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KAUST Repository Item: Exported on 2020-10-01


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