TY - GEN
T1 - Uncalibrated Photometric Stereo Using Superquadrics with Texture Estimation
AU - Migita, Tsuyoshi
AU - Okada, Ayane
AU - Takahashi, Norikazu
N1 - Funding Information:
Supported by JSPS KAKENHI Grant Number 20K11866.
Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - When a 3D scene is captured in several 2D images, a compact description (or parameters) of the 3D scene can be estimated from the images. Such an inference is formulated as the inverse of rendering computer graphics and is important for various applications, such as object recognition, inspection, and/or VR. In the present paper, we extend a photometric stereo method in such a way as to estimate the texture of the object in addition to previous estimation of parameters describing the objects and light sources. To do so, we need a realistic minimization method, combined with a method to obtain the Jacobian of the cost function with respect to the texture. We implemented this method and verified the validity of the framework using synthetic and real-world data.
AB - When a 3D scene is captured in several 2D images, a compact description (or parameters) of the 3D scene can be estimated from the images. Such an inference is formulated as the inverse of rendering computer graphics and is important for various applications, such as object recognition, inspection, and/or VR. In the present paper, we extend a photometric stereo method in such a way as to estimate the texture of the object in addition to previous estimation of parameters describing the objects and light sources. To do so, we need a realistic minimization method, combined with a method to obtain the Jacobian of the cost function with respect to the texture. We implemented this method and verified the validity of the framework using synthetic and real-world data.
KW - Computer graphics
KW - Inverse rendering
KW - Jacobian
KW - Levenberg-Marquardt method
KW - Superquadrics
KW - Two-stage rendering
KW - Uncalibrated photometric stereo
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U2 - 10.1007/978-3-031-06381-7_3
DO - 10.1007/978-3-031-06381-7_3
M3 - Conference contribution
AN - SCOPUS:85131131358
SN - 9783031063800
T3 - Communications in Computer and Information Science
SP - 34
EP - 48
BT - Frontiers of Computer Vision - 28th International Workshop, IW-FCV 2022, Revised Selected Papers
A2 - Sumi, Kazuhiko
A2 - Na, In Seop
A2 - Kaneko, Naoshi
PB - Springer Science and Business Media Deutschland GmbH
T2 - 28th International Workshop on Frontiers of Computer Vision, IW-FCV 2022
Y2 - 21 February 2022 through 22 February 2022
ER -