The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.08 - Aug. (2014 vol.20)
pp: 1200-1213
Aaron Hertzmann , Department of Computer Science , University of Toronto, 10 King’s College Rd, Rm 3302, Toronto, Canada
ABSTRACT
This paper presents an approach for automatically creating graphic design layouts using a new energy-based model derived from design principles. The model includes several new algorithms for analyzing graphic designs, including the prediction of perceived importance, alignment detection, and hierarchical segmentation. Given the model, we use optimization to synthesize new layouts for a variety of single-page graphic designs. Model parameters are learned with Nonlinear Inverse Optimization (NIO) from a small number of example layouts. To demonstrate our approach, we show results for applications including generating design layouts in various styles, retargeting designs to new sizes, and improving existing designs. We also compare our automatic results with designs created using crowdsourcing and show that our approach performs slightly better than novice designers.
INDEX TERMS
Layout, Computational modeling, Optimization, Predictive models, Algorithm design and analysis, Face,nonlinear inverse optimization, Graphic design, layout, modeling, learning, crowdsourcing
CITATION
Aaron Hertzmann, "Learning Layouts for Single-PageGraphic Designs", IEEE Transactions on Visualization & Computer Graphics, vol.20, no. 8, pp. 1200-1213, Aug. 2014, doi:10.1109/TVCG.2014.48
47 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool