Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/645929
Title: Reflectance and Fluorescence Spectral Recovery via Actively Lit RGB Images
Authors: Ying Fu;Antony Lam;Imari Sato;Takahiro Okabe;Yoichi Sato
subject: Varying Illumination|Reflectance and Fluorescence Spectra Recovery|Fluorescent Chromaticity Invariance
Year: 2016
Publisher: IEEE
Abstract: In recent years, fluorescence analysis of scenes has received attention in computer vision. Fluorescence can provide additional information about scenes, and has been used in applications such as camera spectral sensitivity estimation, 3D reconstruction, and color relighting. In particular, hyperspectral images of reflective-fluorescent scenes provide a rich amount of data. However, due to the complex nature of fluorescence, hyperspectral imaging methods rely on specialized equipment such as hyperspectral cameras and specialized illuminants. In this paper, we propose a more practical approach to hyperspectral imaging of reflective-fluorescent scenes using only a conventional RGB camera and varied colored illuminants. The key idea of our approach is to exploit a unique property of fluorescence: the chromaticity of fluorescent emissions are invariant under different illuminants. This allows us to robustly estimate spectral reflectance and fluorescent emission chromaticity. We then show that given the spectral reflectance and fluorescent chromaticity, the fluorescence absorption and emission spectra can also be estimated. We demonstrate in results that all scene spectra can be accurately estimated from RGB images. Finally, we show that our method can be used to accurately relight scenes under novel lighting.
Description: 
URI: http://localhost/handle/Hannan/159749
http://localhost/handle/Hannan/645929
ISSN: 0162-8828
volume: 38
issue: 7
Appears in Collections:2016

Files in This Item:
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Title: Reflectance and Fluorescence Spectral Recovery via Actively Lit RGB Images
Authors: Ying Fu;Antony Lam;Imari Sato;Takahiro Okabe;Yoichi Sato
subject: Varying Illumination|Reflectance and Fluorescence Spectra Recovery|Fluorescent Chromaticity Invariance
Year: 2016
Publisher: IEEE
Abstract: In recent years, fluorescence analysis of scenes has received attention in computer vision. Fluorescence can provide additional information about scenes, and has been used in applications such as camera spectral sensitivity estimation, 3D reconstruction, and color relighting. In particular, hyperspectral images of reflective-fluorescent scenes provide a rich amount of data. However, due to the complex nature of fluorescence, hyperspectral imaging methods rely on specialized equipment such as hyperspectral cameras and specialized illuminants. In this paper, we propose a more practical approach to hyperspectral imaging of reflective-fluorescent scenes using only a conventional RGB camera and varied colored illuminants. The key idea of our approach is to exploit a unique property of fluorescence: the chromaticity of fluorescent emissions are invariant under different illuminants. This allows us to robustly estimate spectral reflectance and fluorescent emission chromaticity. We then show that given the spectral reflectance and fluorescent chromaticity, the fluorescence absorption and emission spectra can also be estimated. We demonstrate in results that all scene spectra can be accurately estimated from RGB images. Finally, we show that our method can be used to accurately relight scenes under novel lighting.
Description: 
URI: http://localhost/handle/Hannan/159749
http://localhost/handle/Hannan/645929
ISSN: 0162-8828
volume: 38
issue: 7
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7115178.pdf12.96 MBAdobe PDFThumbnail
Preview File
Title: Reflectance and Fluorescence Spectral Recovery via Actively Lit RGB Images
Authors: Ying Fu;Antony Lam;Imari Sato;Takahiro Okabe;Yoichi Sato
subject: Varying Illumination|Reflectance and Fluorescence Spectra Recovery|Fluorescent Chromaticity Invariance
Year: 2016
Publisher: IEEE
Abstract: In recent years, fluorescence analysis of scenes has received attention in computer vision. Fluorescence can provide additional information about scenes, and has been used in applications such as camera spectral sensitivity estimation, 3D reconstruction, and color relighting. In particular, hyperspectral images of reflective-fluorescent scenes provide a rich amount of data. However, due to the complex nature of fluorescence, hyperspectral imaging methods rely on specialized equipment such as hyperspectral cameras and specialized illuminants. In this paper, we propose a more practical approach to hyperspectral imaging of reflective-fluorescent scenes using only a conventional RGB camera and varied colored illuminants. The key idea of our approach is to exploit a unique property of fluorescence: the chromaticity of fluorescent emissions are invariant under different illuminants. This allows us to robustly estimate spectral reflectance and fluorescent emission chromaticity. We then show that given the spectral reflectance and fluorescent chromaticity, the fluorescence absorption and emission spectra can also be estimated. We demonstrate in results that all scene spectra can be accurately estimated from RGB images. Finally, we show that our method can be used to accurately relight scenes under novel lighting.
Description: 
URI: http://localhost/handle/Hannan/159749
http://localhost/handle/Hannan/645929
ISSN: 0162-8828
volume: 38
issue: 7
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7115178.pdf12.96 MBAdobe PDFThumbnail
Preview File