Simultaneous Estimation of Spectral Reflectance and Normal from a Small Number of Images

Masahiro Kitahara, Takahiro Okabe, Christian Fuchs, Hendrik P. A. Lensch

Abstract

Spectral reflectance is inherent characteristics of an object surface and therefore useful not only for computer vision tasks such as material classification but also compute graphics applications such as relighting. In this study, by integrating multispectral imaging and photometric stereo, we propose a method for simultaneously estimating the spectral reflectance and normal per pixel from a small number of images taken under multispectral and multidirectional light sources. In addition, taking attached shadows observed on curved surfaces into consideration, we derive the minimum number of images required for the simultaneous estimation and propose a method for selecting the optimal set of light sources. Through a number of experiments using real images, we show that our proposed method can estimate spectral reflectances without the ambiguity of per-pixel scales due to unknown normals, and that, when the optimal set of light sources is used, our method performs as well as the straightforward method using a large number of images. Moreover, we demonstrated that estimating both the spectral reflectances and normals is useful for relighting under novel illumination conditions.

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Paper Citation


in Harvard Style

Kitahara M., Okabe T., Fuchs C. and P. A. Lensch H. (2015). Simultaneous Estimation of Spectral Reflectance and Normal from a Small Number of Images . In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-089-5, pages 303-313. DOI: 10.5220/0005302503030313


in Bibtex Style

@conference{visapp15,
author={Masahiro Kitahara and Takahiro Okabe and Christian Fuchs and Hendrik P. A. Lensch},
title={Simultaneous Estimation of Spectral Reflectance and Normal from a Small Number of Images},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={303-313},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005302503030313},
isbn={978-989-758-089-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015)
TI - Simultaneous Estimation of Spectral Reflectance and Normal from a Small Number of Images
SN - 978-989-758-089-5
AU - Kitahara M.
AU - Okabe T.
AU - Fuchs C.
AU - P. A. Lensch H.
PY - 2015
SP - 303
EP - 313
DO - 10.5220/0005302503030313