An Approximate Shading Model with Detail Decomposition for Object Relighting

Zicheng Liao, Kevin Karsch, Hongyi Zhang, David Forsyth

Research output: Contribution to journalArticle

Abstract

We present an object relighting system that allows an artist to select an object from an image and insert it into a target scene. Through simple interactions, the system can adjust illumination on the inserted object so that it appears naturally in the scene. To support image-based relighting, we build object model from the image, and propose a perceptually-inspired approximate shading model for the relighting. It decomposes the shading field into (a) a rough shape term that can be reshaded, (b) a parametric shading detail that encodes missing features from the first term, and (c) a geometric detail term that captures fine-scale material properties. With this decomposition, the shading model combines 3D rendering and image-based composition and allows more flexible compositing than image-based methods. Quantitative evaluation and a set of user studies suggest our method is a promising alternative to existing methods of object insertion.

Original languageEnglish (US)
Pages (from-to)22-37
Number of pages16
JournalInternational Journal of Computer Vision
Volume127
Issue number1
DOIs
StatePublished - Jan 15 2019

Keywords

  • Image relighting
  • Image-based modeling
  • Object insertion
  • Shading model

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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