Multispectral Photometric Stereo for Spatially-Varying Spectral Reflectances
Multispectral Photometric Stereo for Spatially-Varying Spectral Reflectances
复制标题
用于空间变化光谱反射率的多光谱光度立体
DOI:
10.1007/s11263-022-01634-4
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发表时间:
2022
期刊:
影响因子:
--
通讯作者:
and Yasuyuki Matsushita
中科院分区:
文献类型:
--
作者:
Heng Guo;Fumio Okura;Boxin Shi;Takuya Funatomi;Yasuhiro Mukaigawa;and Yasuyuki Matsushita
Multispectral photometric stereo (MPS) aims at recovering the surface normal of a scene measured under multiple light sources with different wavelengths. While it opens up a capability of a single-shot measurement of surface normal, the problem has been known ill-posed. To make the problem well-posed, existing MPS methods rely on restrictive assumptions, such as shape prior, surfaces having a monochromatic with uniform albedo. This paper alleviates these restrictive assumptions in existing methods. We show that the problem becomes well-posed for surfaces with uniform chromaticity but spatially-varying albedos based on our new formulation. Specifically, if at least three (or two) scene points share the same chromaticity, the proposed method uniquely recovers their surface normals with the illumination of no less than four (or five) spectral lights in a closed-form. In addition, we show that a more general setting of spatially-varying both chromaticities and albedos can become well-posed if the light spectra and camera spectral sensitivity are calibrated. For this general setting, we derive a unique and closed-form solution for MPS using the linear bases extracted from a spectral reflectance database. Experiments on both synthetic and real captured data with spatially-varying reflectance demonstrate the effectiveness of our method and show the potential applicability for multispectral heritage preservation.
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影响因子:
4.5
作者:
Ozawa, Keisuke;Sato, Imari;Yamaguchi, Masahiro
通讯作者:
Yamaguchi, Masahiro
DOI:
--
发表时间:
2003
期刊:
影响因子:
--
作者:
M. Hain;J. Bartl;V. Jacko
通讯作者:
V. Jacko
DOI:
10.1109/cvprw.2019.00065
发表时间:
2019
期刊:
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
影响因子:
--
作者:
Doris Antensteiner;S. Stolc;Daniel Soukup
通讯作者:
Daniel Soukup
DOI:
10.1007/bf02289573
发表时间:
1963
期刊:
影响因子:
--
作者:
R. M. Johnson
通讯作者:
R. M. Johnson
DOI:
10.1109/34.888718
发表时间:
2000-11-01
影响因子:
23.6
作者:
Zhang, ZY
通讯作者:
Zhang, ZY