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Automatic Scene Inference for 3D Object Compositing.

Authors :
KARSCH, KEVIN
SUNKAVALLI, KALYAN
HADAP, SUNIL
CARR, NATHAN
HAILIN JIN
FONTE, RAFAEL
SITTIG, MICHAEL
FORSYTH, DAVID
Source :
ACM Transactions on Graphics; 2014, Vol. 33 Issue 3, p32-32:15, 15p, 1 Chart
Publication Year :
2014

Abstract

We present a user-friendly image editing system that supports a drag-and-drop object insertion (where the user merely drags objects into the image, and the system automatically places them in 3D and relights them appropriately), postprocess illumination editing, and depth-of-field manipulation. Underlying our system is a fully automatic technique for recovering a comprehensive 3D scene model (geometry, illumination, diffuse albedo, and camera parameters) from a single, low dynamic range photograph. This is made possible by two novel contributions: an illumination inference algorithm that recovers a full lighting model of the scene (including light sources that are not directly visible in the photograph), and a depth estimation algorithm that combines data-driven depth transfer with geometric reasoning about the scene layout. A user study shows that our system produces perceptually convincing results, and achieves the same level of realism as techniques that require significant user interaction. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
07300301
Volume :
33
Issue :
3
Database :
Complementary Index
Journal :
ACM Transactions on Graphics
Publication Type :
Academic Journal
Accession number :
96675533
Full Text :
https://doi.org/10.1145/2602146