Automatic Constraint Detection for 2D Layout Regularization

Handle URI:
http://hdl.handle.net/10754/578820
Title:
Automatic Constraint Detection for 2D Layout Regularization
Authors:
Jiang, Haiyong; Nan, Liangliang ( 0000-0002-5629-9975 ) ; Yan, Dongming ( 0000-0003-2209-2404 ) ; Dong, Weiming; Zhang, Xiaopeng; Wonka, Peter ( 0000-0003-0627-9746 )
Abstract:
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.
KAUST Department:
Visual Computing Center (VCC)
Citation:
Automatic Constraint Detection for 2D Layout Regularization 2015:1 IEEE Transactions on Visualization and Computer Graphics
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
IEEE Transactions on Visualization and Computer Graphics
Issue Date:
18-Sep-2015
DOI:
10.1109/TVCG.2015.2480059
Type:
Article
ISSN:
1077-2626
Additional Links:
http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7272131
Appears in Collections:
Articles; Visual Computing Center (VCC)

Full metadata record

DC FieldValue Language
dc.contributor.authorJiang, Haiyongen
dc.contributor.authorNan, Liangliangen
dc.contributor.authorYan, Dongmingen
dc.contributor.authorDong, Weimingen
dc.contributor.authorZhang, Xiaopengen
dc.contributor.authorWonka, Peteren
dc.date.accessioned2015-09-28T13:55:51Zen
dc.date.available2015-09-28T13:55:51Zen
dc.date.issued2015-09-18en
dc.identifier.citationAutomatic Constraint Detection for 2D Layout Regularization 2015:1 IEEE Transactions on Visualization and Computer Graphicsen
dc.identifier.issn1077-2626en
dc.identifier.doi10.1109/TVCG.2015.2480059en
dc.identifier.urihttp://hdl.handle.net/10754/578820en
dc.description.abstractIn 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.en
dc.language.isoenen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7272131en
dc.rights(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.en
dc.titleAutomatic Constraint Detection for 2D Layout Regularizationen
dc.typeArticleen
dc.contributor.departmentVisual Computing Center (VCC)en
dc.identifier.journalIEEE Transactions on Visualization and Computer Graphicsen
dc.eprint.versionPost-printen
dc.contributor.institutionNational Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences, Beijing 100190, Chinaen
dc.contributor.institutionArizona State University, Tempe, AZen
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorJiang, Haiyongen
kaust.authorNan, Liangliangen
kaust.authorYan, Dongmingen
kaust.authorWonka, Peteren
All Items in KAUST are protected by copyright, with all rights reserved, unless otherwise indicated.