Surface reflectance and normal estimation from photometric stereo

Qingxiong Yang, Narendra Ahuja

Research output: Contribution to journalArticle

Abstract

In this paper, we propose a new photometric stereo method for estimating diffuse reflection and surface normal from color images. Using dichromatic reflection model, we introduce surface chromaticity as a matching invariant for photometric stereo, which serves as the foundation of the theory of this paper. An extremely simple and robust reflection components separation method is proposed based on the invariant. Our separation method differs from most previous methods which either assume dependencies among pixels or require segmentation. We also show that a linear relationship between the image color and the surface normal can be obtained based on this invariant. The linear relationship turns the surface normal estimation problem into a linear system that can be solved exactly or via least-squares optimization. We present experiments on both synthetic and real images, which demonstrate the effectiveness of our method.

Original languageEnglish (US)
Pages (from-to)793-802
Number of pages10
JournalComputer Vision and Image Understanding
Volume116
Issue number7
DOIs
StatePublished - Jul 1 2012

Keywords

  • Chromaticity
  • Dichromatic reflection model
  • Photometric stereo
  • Reflection components separation
  • Specular reflection

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition

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