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article · 2023

Optical properties reconstruction with differentiable rendering

Igor Kinev, Anatoly Lysykh, Dmitry Zhdanov, Korlan Argynova, Igor S. Potemin, Вадим Соколов, Андрей Жданов

Cited by 0Abstract and details only

Abstract

Currently, for most VR/AR applications it is necessary to reconstruct physically-correctly the real world, and the optical properties of objects. In this paper, to solve this problem, we propose to use a parametric model of optical properties, which is a mix of several known models, which has a small number of parameters and correctly simulates the propagation of light in the scene. In addition, based on the parameters of the model, differential rendering of the image is performed, as a result of which the obtained differentials can be further used in the optimizer. The optimizer, in turn, can modify the model parameters to improve the rendering quality and thus bring the proposed model of optical properties closer to the real optical properties of objects.

Cite this paper

APA 7

Kinev, I., Lysykh, A., Zhdanov, D., Argynova, K., Potemin, I. S., Соколов, В., & Жданов, А. (2023). Optical properties reconstruction with differentiable rendering. https://doi.org/10.1117/12.2688285

MLA 9

Kinev, Igor, et al. “Optical properties reconstruction with differentiable rendering.” vol. 1, 2023, p. 59, https://doi.org/10.1117/12.2688285.

Chicago

Kinev, Igor, Anatoly Lysykh, Dmitry Zhdanov, Korlan Argynova, Igor S. Potemin, Вадим Соколов, and Андрей Жданов. 2023. “Optical properties reconstruction with differentiable rendering.” https://doi.org/10.1117/12.2688285.

Harvard

Kinev, I. et al. (2023) ‘Optical properties reconstruction with differentiable rendering’. Available at: https://doi.org/10.1117/12.2688285.

BibTeX
@article{kinev2023optical,
  title = {{Optical properties reconstruction with differentiable rendering}},
  author = {Kinev, Igor and Lysykh, Anatoly and Zhdanov, Dmitry and Argynova, Korlan and Potemin, Igor S. and Соколов, Вадим and Жданов, Андрей},
  volume = {1},
  pages = {59},
  year = {2023},
  doi = {10.1117/12.2688285}
}

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