Automatic Constraint Detection for 2D Layout Regularization

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

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


In this paper, we address the problem of constraint detection for layout regularization. The layout we consider is a set of two-dimensional elements where each element is represented by its bounding box. Layout regularization is important in digitizing plans or images, such as floor plans and facade images, and in 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 layout regularization as a quadratic programming problem. In addition, we propose a novel optimization algorithm that automatically detects constraints. We evaluate the proposed framework using a variety of input layouts from different applications. Our results demonstrate that our method has superior performance to the state of the art.

Original languageEnglish (US)
Article number7272131
Pages (from-to)1933-1944
Number of pages12
JournalIEEE Transactions on Visualization and Computer Graphics
Issue number8
StatePublished - Aug 1 2016
Externally publishedYes


  • Layout regularization
  • constraint analysis
  • constraint detection
  • linear integer programming

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design


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