Reflectance and Shape Estimation with a Light Field Camera Under Natural Illumination

Reflectance and shape are two important components in visually perceiving the real world. Inferring the reflectance and shape of an object through cameras is a fundamental research topic in the field of computer vision. While three-dimensional shape recovery is pervasive with varieties of approaches...

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Veröffentlicht in:	International journal of computer vision Jg. 127; H. 11-12; S. 1707 - 1722
Hauptverfasser:	Ngo, Thanh-Trung, Nagahara, Hajime, Nishino, Ko, Taniguchi, Rin-ichiro, Yagi, Yasushi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.12.2019 Springer Springer Nature B.V
Schlagworte:	Artificial Intelligence Cameras Computer Imaging Computer Science Computer simulation Computer vision Field cameras Illumination Image Processing and Computer Vision Light Machine vision Measurement Pattern Recognition Pattern Recognition and Graphics Radiation Recovery Reflectance Vision Shape from shading Light field camera Natural illumination Reflectance
ISSN:	0920-5691, 1573-1405
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Abstract	Reflectance and shape are two important components in visually perceiving the real world. Inferring the reflectance and shape of an object through cameras is a fundamental research topic in the field of computer vision. While three-dimensional shape recovery is pervasive with varieties of approaches and practical applications, reflectance recovery has only emerged recently. Reflectance recovery is a challenging task that is usually conducted in controlled environments, such as a laboratory environment with a special apparatus. However, it is desirable that the reflectance be recovered in the field with a handy camera so that reflectance can be jointly recovered with the shape. To that end, we present a solution that simultaneously recovers the reflectance and shape (i.e., dense depth and normal maps) of an object under natural illumination with commercially available handy cameras. We employ a light field camera to capture one light field image of the object, and a 360-degree camera to capture the illumination. The proposed method provides positive results in both simulation and real-world experiments.
AbstractList	Reflectance and shape are two important components in visually perceiving the real world. Inferring the reflectance and shape of an object through cameras is a fundamental research topic in the field of computer vision. While three-dimensional shape recovery is pervasive with varieties of approaches and practical applications, reflectance recovery has only emerged recently. Reflectance recovery is a challenging task that is usually conducted in controlled environments, such as a laboratory environment with a special apparatus. However, it is desirable that the reflectance be recovered in the field with a handy camera so that reflectance can be jointly recovered with the shape. To that end, we present a solution that simultaneously recovers the reflectance and shape (i.e., dense depth and normal maps) of an object under natural illumination with commercially available handy cameras. We employ a light field camera to capture one light field image of the object, and a 360-degree camera to capture the illumination. The proposed method provides positive results in both simulation and real-world experiments.
Audience	Academic
Author	Nishino, Ko Yagi, Yasushi Taniguchi, Rin-ichiro Ngo, Thanh-Trung Nagahara, Hajime
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CitedBy_id	crossref_primary_10_1016_j_neucom_2022_06_096 crossref_primary_10_1016_j_patcog_2020_107724 crossref_primary_10_1007_s11263_020_01367_2
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Snippet	Reflectance and shape are two important components in visually perceiving the real world. Inferring the reflectance and shape of an object through cameras is a...
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SubjectTerms	Artificial Intelligence Cameras Computer Imaging Computer Science Computer simulation Computer vision Field cameras Illumination Image Processing and Computer Vision Light Machine vision Measurement Pattern Recognition Pattern Recognition and Graphics Radiation Recovery Reflectance Vision
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Title	Reflectance and Shape Estimation with a Light Field Camera Under Natural Illumination
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