Composition-Aware Scene Optimization for Product Images

Increasingly, companies are creating product advertisements and catalog images using computer renderings of 3D scenes. A common goal for these companies is to create aesthetically appealing compositions that highlight objects of interest within the context of a scene. Unfortunately, this goal is cha...

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Veröffentlicht in:Computer graphics forum Jg. 34; H. 2; S. 13 - 24
Hauptverfasser: Liu, Tianqiang, McCann, Jim, Li, Wilmot, Funkhouser, Thomas
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Oxford Blackwell Publishing Ltd 01.05.2015
Schlagworte:
3-D graphics
Advertisements
Analysis
Cameras
Categories and Subject Descriptors (according to ACM CCS)
I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling-Physically based modeling
I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism-Animation
Image processing systems
Optimization
Placement
Studies
Three dimensional
ISSN:0167-7055, 1467-8659
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Zusammenfassung:Increasingly, companies are creating product advertisements and catalog images using computer renderings of 3D scenes. A common goal for these companies is to create aesthetically appealing compositions that highlight objects of interest within the context of a scene. Unfortunately, this goal is challenging, not only due to the need to balance the trade‐off among aesthetic principles and design constraints, but also because of the huge search space induced by possible camera parameters, object placement, material choices, etc. Previous methods have investigated only optimization of camera parameters. In this paper, we develop a tool that starts from an initial scene description and a set of high‐level constraints provided by a stylist and then automatically generates an optimized scene whose 2D composition is improved. It does so by locally adjusting the 3D object transformations, surface materials, and camera parameters. The value of this tool is demonstrated in a variety of applications motivated by product catalogs, including rough layout refinement, detail image creation, home planning, cultural customization, and text inlay placement. Results of a perceptual study indicate that our system produces images preferable for product advertisement compared to a more traditional camera‐only optimization.
Bibliographie:Supporting InformationSupporting Information
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ArticleID:CGF12537
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ISSN:0167-7055
1467-8659
DOI:10.1111/cgf.12537