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.
- Image processing
- photometric stereo
- sphere detection
- light calibration
Liao, J., Buchholz, B., Thiery, J-M., Bauszat, P., & Eisemann, E. (2017). Indoor Scene Reconstruction Using Near-light Photometric Stereo. IEEE Transactions on Image Processing, 26(3), 1089-1101. https://doi.org/10.1109/TIP.2016.2636661