Indoor Scene Reconstruction Using Near-light Photometric Stereo

Jingtang Liao, Bert Buchholz, Jean-Marc Thiery, Pablo Bauszat, Elmar Eisemann

Research output: Contribution to journalArticleScientificpeer-review

13 Citations (Scopus)


We propose a novel framework for photometric stereo (PS) under low-light conditions using uncalibrated near-light illumination. It operates on free-form video sequences captured with a minimalistic and affordable setup. We address issues such as albedo variations, shadowing, perspective projections, and camera noise. Our method uses specular spheres detected with a perspective-correcting Hough transform to robustly triangulate light positions in the presence of outliers via a least-squares approach. Furthermore, we propose an iterative reweighting scheme in combination with an ℓp-norm minimizer to robustly solve the calibrated near-light PS problem. In contrast to other approaches, our framework reconstructs depth, albedo (relative to light source intensity), and normals simultaneously and is demonstrated on synthetic and real-world scenes.
Original languageEnglish
Pages (from-to)1089-1101
Number of pages23
JournalIEEE Transactions on Image Processing
Issue number3
Publication statusPublished - 2017


  • albedo
  • Image processing
  • photometric stereo
  • near-light
  • sphere detection
  • light calibration
  • normal
  • depth


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