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Colour Helmholtz Stereopsis for Reconstruction of Dynamic Scenes with Arbitrary Unknown Reflectance
Helmholtz Stereopsis is a powerful technique for reconstruction of scenes with arbitrary reflectance properties. However, previous formulations have been limited to static objects due to the requirement to sequentially capture reciprocal image pairs (i.e. two images with the camera and light source...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6979544/ https://www.ncbi.nlm.nih.gov/pubmed/32025092 http://dx.doi.org/10.1007/s11263-016-0951-0 |
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author | Roubtsova, Nadejda Guillemaut, Jean-Yves |
author_facet | Roubtsova, Nadejda Guillemaut, Jean-Yves |
author_sort | Roubtsova, Nadejda |
collection | PubMed |
description | Helmholtz Stereopsis is a powerful technique for reconstruction of scenes with arbitrary reflectance properties. However, previous formulations have been limited to static objects due to the requirement to sequentially capture reciprocal image pairs (i.e. two images with the camera and light source positions mutually interchanged). In this paper, we propose colour Helmholtz Stereopsis—a novel framework for Helmholtz Stereopsis based on wavelength multiplexing. To address the new set of challenges introduced by multispectral data acquisition, the proposed Colour Helmholtz Stereopsis pipeline uniquely combines a tailored photometric calibration for multiple camera/light source pairs, a novel procedure for spatio-temporal surface chromaticity calibration and a state-of-the-art Bayesian formulation necessary for accurate reconstruction from a minimal number of reciprocal pairs. In this framework, reflectance is spatially unconstrained both in terms of its chromaticity and the directional component dependent on the illumination incidence and viewing angles. The proposed approach for the first time enables modelling of dynamic scenes with arbitrary unknown and spatially varying reflectance using a practical acquisition set-up consisting of a small number of cameras and light sources. Experimental results demonstrate the accuracy and flexibility of the technique on a variety of static and dynamic scenes with arbitrary unknown BRDF and chromaticity ranging from uniform to arbitrary and spatially varying. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11263-016-0951-0) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6979544 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-69795442020-02-03 Colour Helmholtz Stereopsis for Reconstruction of Dynamic Scenes with Arbitrary Unknown Reflectance Roubtsova, Nadejda Guillemaut, Jean-Yves Int J Comput Vis Article Helmholtz Stereopsis is a powerful technique for reconstruction of scenes with arbitrary reflectance properties. However, previous formulations have been limited to static objects due to the requirement to sequentially capture reciprocal image pairs (i.e. two images with the camera and light source positions mutually interchanged). In this paper, we propose colour Helmholtz Stereopsis—a novel framework for Helmholtz Stereopsis based on wavelength multiplexing. To address the new set of challenges introduced by multispectral data acquisition, the proposed Colour Helmholtz Stereopsis pipeline uniquely combines a tailored photometric calibration for multiple camera/light source pairs, a novel procedure for spatio-temporal surface chromaticity calibration and a state-of-the-art Bayesian formulation necessary for accurate reconstruction from a minimal number of reciprocal pairs. In this framework, reflectance is spatially unconstrained both in terms of its chromaticity and the directional component dependent on the illumination incidence and viewing angles. The proposed approach for the first time enables modelling of dynamic scenes with arbitrary unknown and spatially varying reflectance using a practical acquisition set-up consisting of a small number of cameras and light sources. Experimental results demonstrate the accuracy and flexibility of the technique on a variety of static and dynamic scenes with arbitrary unknown BRDF and chromaticity ranging from uniform to arbitrary and spatially varying. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11263-016-0951-0) contains supplementary material, which is available to authorized users. Springer US 2016-09-20 2017 /pmc/articles/PMC6979544/ /pubmed/32025092 http://dx.doi.org/10.1007/s11263-016-0951-0 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Article Roubtsova, Nadejda Guillemaut, Jean-Yves Colour Helmholtz Stereopsis for Reconstruction of Dynamic Scenes with Arbitrary Unknown Reflectance |
title | Colour Helmholtz Stereopsis for Reconstruction of Dynamic Scenes with Arbitrary Unknown Reflectance |
title_full | Colour Helmholtz Stereopsis for Reconstruction of Dynamic Scenes with Arbitrary Unknown Reflectance |
title_fullStr | Colour Helmholtz Stereopsis for Reconstruction of Dynamic Scenes with Arbitrary Unknown Reflectance |
title_full_unstemmed | Colour Helmholtz Stereopsis for Reconstruction of Dynamic Scenes with Arbitrary Unknown Reflectance |
title_short | Colour Helmholtz Stereopsis for Reconstruction of Dynamic Scenes with Arbitrary Unknown Reflectance |
title_sort | colour helmholtz stereopsis for reconstruction of dynamic scenes with arbitrary unknown reflectance |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6979544/ https://www.ncbi.nlm.nih.gov/pubmed/32025092 http://dx.doi.org/10.1007/s11263-016-0951-0 |
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