Automatic Scene Inference for 3D Object Compositing

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.

Document Details

Document Type
Pub Defense Publication
Publication Date
May 01, 2014
Source ID
10.1145/2602146

Entities

People

  • David Forsyth
  • Hailin Jin
  • Kalyan Sunkavalli
  • Kevin Karsch
  • Michael Sittig
  • Nathan Carr
  • Rafael Fonte
  • Sunil Hadap

Organizations

  • Adobe
  • Division of Information and Intelligent Systems
  • National Science Foundation
  • Office of Naval Research
  • University of Illinois Urbana–Champaign

Tags

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Database Systems and Applications

Technology Areas

  • AI & ML