Semi-calibrated near-light photometric stereo
Queau Y, Wu T, Cremers D (2017)
Publication Type: Conference contribution
Publication year: 2017
Journal
Publisher: Springer Verlag
Book Volume: 10302 LNCS
Pages Range: 656-668
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Kolding, DNK
ISBN: 9783319587707
DOI: 10.1007/978-3-319-58771-4_52
Abstract
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.
Involved external institutions
Germany (DE)How to cite
APA:
Queau, Y., Wu, T., & Cremers, D. (2017). Semi-calibrated near-light photometric stereo. In Francois Lauze, Yiqiu Dong, Anders Bjorholm Dahl (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 656-668). Kolding, DNK: Springer Verlag.
MLA:
Queau, Yvain, Tao Wu, and Daniel Cremers. "Semi-calibrated near-light photometric stereo." Proceedings of the 6th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2017, Kolding, DNK Ed. Francois Lauze, Yiqiu Dong, Anders Bjorholm Dahl, Springer Verlag, 2017. 656-668.
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