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Uncalibrated Photometric Stereo Using Superquadrics with Texture Estimation

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Frontiers of Computer Vision (IW-FCV 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1578))

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Abstract

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.

Supported by JSPS KAKENHI Grant Number 20K11866.

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Authors and Affiliations

  1. Okayama University, Okayama, Japan

    Tsuyoshi Migita, Ayane Okada & Norikazu Takahashi

Authors
  1. Tsuyoshi Migita
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  2. Ayane Okada
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  3. Norikazu Takahashi
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Corresponding author

Correspondence to Tsuyoshi Migita .

Editor information

Editors and Affiliations

  1. Aoyama Gakuin University, Kanagawa, Japan

    Kazuhiko Sumi

  2. Chosun University, Gwangju, Korea (Republic of)

    In Seop Na

  3. Aoyama Gakuin University, Kanagawa, Japan

    Naoshi Kaneko

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Migita, T., Okada, A., Takahashi, N. (2022). Uncalibrated Photometric Stereo Using Superquadrics with Texture Estimation. In: Sumi, K., Na, I.S., Kaneko, N. (eds) Frontiers of Computer Vision. IW-FCV 2022. Communications in Computer and Information Science, vol 1578. Springer, Cham. https://doi.org/10.1007/978-3-031-06381-7_3

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  • DOI: https://doi.org/10.1007/978-3-031-06381-7_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-06380-0

  • Online ISBN: 978-3-031-06381-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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