TY - CHAP
T1 - Photometric Stereo
AU - Ikeuchi, Katsushi
AU - Matsushita, Yasuyuki
AU - Sagawa, Ryusuke
AU - Kawasaki, Hiroshi
AU - Mukaigawa, Yasuhiro
AU - Furukawa, Ryo
AU - Miyazaki, Daisuke
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020
Y1 - 2020
N2 - Shading on a surface provides strong cues for us to perceive the 3D shape of an object. The study of computationally inferring a 3D shape from shading cues originated with shape from shading (Horn in Shape from shading: a method for obtaining the shape of a smooth opaque object from one view. Technical report, 1970, [1], Ikeuchi and Horn in Artif Intell 17(1–3):141–184, 1981, [2]), which aims to estimate a 3D shape from a single image observed under a light source. The problem has attracted many researchers’ attentions since then because of its mathematically rich problem structure and important practical applications. Later, it was shown that, instead of a single image, the use of multiple images observed under different lighting conditions could alleviate the difficulty of the problem of 3D shape estimation from shading cues. This multiple-image approach is known as photometric stereo. This chapter describes the problem of photometric stereo and its solution methods.
AB - Shading on a surface provides strong cues for us to perceive the 3D shape of an object. The study of computationally inferring a 3D shape from shading cues originated with shape from shading (Horn in Shape from shading: a method for obtaining the shape of a smooth opaque object from one view. Technical report, 1970, [1], Ikeuchi and Horn in Artif Intell 17(1–3):141–184, 1981, [2]), which aims to estimate a 3D shape from a single image observed under a light source. The problem has attracted many researchers’ attentions since then because of its mathematically rich problem structure and important practical applications. Later, it was shown that, instead of a single image, the use of multiple images observed under different lighting conditions could alleviate the difficulty of the problem of 3D shape estimation from shading cues. This multiple-image approach is known as photometric stereo. This chapter describes the problem of photometric stereo and its solution methods.
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U2 - 10.1007/978-3-030-56577-0_5
DO - 10.1007/978-3-030-56577-0_5
M3 - Chapter
AN - SCOPUS:85091155976
T3 - Advances in Computer Vision and Pattern Recognition
SP - 107
EP - 123
BT - Advances in Computer Vision and Pattern Recognition
PB - Springer Science and Business Media Deutschland GmbH
ER -