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SceneSuggest: Context-driven 3D Scene Design

Authors :
Savva, Manolis
Chang, Angel X.
Agrawala, Maneesh
Publication Year :
2017

Abstract

We present SceneSuggest: an interactive 3D scene design system providing context-driven suggestions for 3D model retrieval and placement. Using a point-and-click metaphor we specify regions in a scene in which to automatically place and orient relevant 3D models. Candidate models are ranked using a set of static support, position, and orientation priors learned from 3D scenes. We show that our suggestions enable rapid assembly of indoor scenes. We perform a user study comparing suggestions to manual search and selection, as well as to suggestions with no automatic orientation. We find that suggestions reduce total modeling time by 32%, that orientation priors reduce time spent re-orienting objects by 27%, and that context-driven suggestions reduce the number of text queries by 50%.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.1703.00061
Document Type :
Working Paper