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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Bibliographic Details
Published in:International journal of computer vision Vol. 127; no. 11-12; pp. 1707 - 1722
Main Authors: Ngo, Thanh-Trung, Nagahara, Hajime, Nishino, Ko, Taniguchi, Rin-ichiro, Yagi, Yasushi
Format: Journal Article
Language:English
Published: New York Springer US 01.12.2019
Springer
Springer Nature B.V
Subjects:
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
Online Access:Get full text
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Summary: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.
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ISSN:0920-5691
1573-1405
DOI:10.1007/s11263-019-01149-5