Indoor Scene Reconstruction Using Near-light Photometric Stereo

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 l_p-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.

@Article { LBTBE17,
  author       = "Liao, Jingtang and Buchholz, Bert and Thiery, Jean-Marc and Bauszat, Pablo and Eisemann, Elmar",
  title        = "Indoor Scene Reconstruction Using Near-light Photometric Stereo",
  journal      = "IEEE Transactions on Image Processing",
  number       = "3",
  volume       = "26",
  pages        = "1089-1101",
  month        = "March",
  year         = "2017",
  note         = "DOI: 10.1109/TIP.2016.2636661",
  url          = "http://graphics.tudelft.nl/Publications-new/2017/LBTBE17"
}