Automatic Scene Inference for 3D Object Compositing

Author:

Karsch Kevin1,Sunkavalli Kalyan2,Hadap Sunil2,Carr Nathan2,Jin Hailin2,Fonte Rafael1,Sittig Michael1,Forsyth David1

Affiliation:

1. University of Illinois

2. Adobe Research

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.

Funder

Office of Naval Research

National Science Foundation

Division of Information and Intelligent Systems

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design

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