Non-parametric filtering for geometric detail extraction and material representation

Zicheng Liao, Jason Rock, Yang Wang, David Forsyth

Research output: Contribution to journalConference article

Abstract

Geometric detail is a universal phenomenon in real world objects. It is an important component in object modeling, but not accounted for in current intrinsic image works. In this work, we explore using a non-parametric method to separate geometric detail from intrinsic image components. We further decompose an image as albedo * (coarse-scale shading + shading detail). Our decomposition offers quantitative improvement in albedo recovery and material classification. Our method also enables interesting image editing activities, including bump removal, geometric detail smoothing/enhancement and material transfer.

Original languageEnglish (US)
Article number6618973
Pages (from-to)963-970
Number of pages8
JournalProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
DOIs
StatePublished - Nov 15 2013
Event26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2013 - Portland, OR, United States
Duration: Jun 23 2013Jun 28 2013

Keywords

  • Geometric detail
  • intrinsic image decomposition
  • material representation

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

Fingerprint Dive into the research topics of 'Non-parametric filtering for geometric detail extraction and material representation'. Together they form a unique fingerprint.

  • Cite this