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A L1-TV algorithm for robust perspective photometric stereo with spatially-varying lightings. / Quéau, Yvain; Lauze, Francois Bernard; Durou, Jean-Denis.
Scale space and variational methods in computer vision: 5th International Conference, SSVM 2015, Lège-Cap Ferret, France, May 31 - June 4, 2015, Proceedings. Springer, 2015. s. 498-510 (Lecture notes in computer science, Bind 9087).
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
Harvard
Quéau, Y
, Lauze, FB & Durou, J-D 2015,
A L1-TV algorithm for robust perspective photometric stereo with spatially-varying lightings. i
Scale space and variational methods in computer vision: 5th International Conference, SSVM 2015, Lège-Cap Ferret, France, May 31 - June 4, 2015, Proceedings. Springer, Lecture notes in computer science, bind 9087, s. 498-510, International Conference, SSVM 2015, Lège-Cap Ferret, Frankrig,
31/05/2015.
https://doi.org/10.1007/978-3-319-18461-6_40APA
Quéau, Y.
, Lauze, F. B., & Durou, J-D. (2015).
A L1-TV algorithm for robust perspective photometric stereo with spatially-varying lightings. I
Scale space and variational methods in computer vision: 5th International Conference, SSVM 2015, Lège-Cap Ferret, France, May 31 - June 4, 2015, Proceedings (s. 498-510). Springer. Lecture notes in computer science Bind 9087
https://doi.org/10.1007/978-3-319-18461-6_40Vancouver
Quéau Y
, Lauze FB, Durou J-D.
A L1-TV algorithm for robust perspective photometric stereo with spatially-varying lightings. I Scale space and variational methods in computer vision: 5th International Conference, SSVM 2015, Lège-Cap Ferret, France, May 31 - June 4, 2015, Proceedings. Springer. 2015. s. 498-510. (Lecture notes in computer science, Bind 9087).
https://doi.org/10.1007/978-3-319-18461-6_40Author
Quéau, Yvain ; Lauze, Francois Bernard ; Durou, Jean-Denis. / A L1-TV algorithm for robust perspective photometric stereo with spatially-varying lightings. Scale space and variational methods in computer vision: 5th International Conference, SSVM 2015, Lège-Cap Ferret, France, May 31 - June 4, 2015, Proceedings. Springer, 2015. s. 498-510 (Lecture notes in computer science, Bind 9087).
Bibtex
@inproceedings{c62ae56ba2d345239f601ce5a69ded43,
title = "A L1-TV algorithm for robust perspective photometric stereo with spatially-varying lightings",
abstract = "We tackle the problem of perspective 3D-reconstruction of Lambertian surfaces through photometric stereo, in the presence of outliers to Lambert's law, depth discontinuities, and unknown spatially-varying lightings. To this purpose, we introduce a robust $L^1$-TV variational formulation of the recovery problem where the shape itself is the main unknown, which naturally enforces integrability and permits to avoid integrating the normal field. ",
author = "Yvain Qu{\'e}au and Lauze, {Francois Bernard} and Jean-Denis Durou",
year = "2015",
doi = "10.1007/978-3-319-18461-6_40",
language = "English",
isbn = "978-3-319-18460-9",
series = "Lecture notes in computer science",
publisher = "Springer",
pages = "498--510",
booktitle = "Scale space and variational methods in computer vision",
address = "Switzerland",
note = "null ; Conference date: 31-05-2015 Through 04-06-2015",
}
RIS
TY - GEN
T1 - A L1-TV algorithm for robust perspective photometric stereo with spatially-varying lightings
AU - Quéau, Yvain
AU - Lauze, Francois Bernard
AU - Durou, Jean-Denis
PY - 2015
Y1 - 2015
N2 - We tackle the problem of perspective 3D-reconstruction of Lambertian surfaces through photometric stereo, in the presence of outliers to Lambert's law, depth discontinuities, and unknown spatially-varying lightings. To this purpose, we introduce a robust $L^1$-TV variational formulation of the recovery problem where the shape itself is the main unknown, which naturally enforces integrability and permits to avoid integrating the normal field.
AB - We tackle the problem of perspective 3D-reconstruction of Lambertian surfaces through photometric stereo, in the presence of outliers to Lambert's law, depth discontinuities, and unknown spatially-varying lightings. To this purpose, we introduce a robust $L^1$-TV variational formulation of the recovery problem where the shape itself is the main unknown, which naturally enforces integrability and permits to avoid integrating the normal field.
U2 - 10.1007/978-3-319-18461-6_40
DO - 10.1007/978-3-319-18461-6_40
M3 - Article in proceedings
SN - 978-3-319-18460-9
T3 - Lecture notes in computer science
SP - 498
EP - 510
BT - Scale space and variational methods in computer vision
PB - Springer
Y2 - 31 May 2015 through 4 June 2015
ER -
