Semi-calibrated near-light photometric stereo

We tackle the nonlinear problem of photometric stereo under close-range pointwise sources, when the intensities of the sources are unknown (so-called semi-calibrated setup). A variational approach aiming at robust joint recovery of depth, albedo and intensities is proposed. The resulting nonconvex model is numerically resolved by a provably convergent alternating minimization scheme, where the construction of each subproblem utilizes an iteratively reweighted least-squares approach. In particular, manifold optimization technique is used in solving the corresponding subproblems over the rank-1 matrix manifold. Experiments on real-world datasets demonstrate that the new approach provides not only theoretical guarantees on convergence, but also more accurate geometry.