Optical properties reconstruction with differentiable rendering

Igor Kinev; Anatoly Lysykh; Dmitry Zhdanov; Korlan Argynova; Igor Potemin; Vadim Sokolov; Andrei Zhdanov

doi:10.1117/12.2688285

27 November 2023 Optical properties reconstruction with differentiable rendering

Igor Kinev, Anatoly Lysykh, Dmitry Zhdanov, Korlan Argynova, Igor Potemin, Vadim Sokolov, Andrei Zhdanov

Proceedings Volume 12767, Optoelectronic Imaging and Multimedia Technology X; 127671L (2023) https://doi.org/10.1117/12.2688285
Event: SPIE/COS Photonics Asia, 2023, Beijing, China

Conference Poster

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.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Igor Kinev, Anatoly Lysykh, Dmitry Zhdanov, Korlan Argynova, Igor Potemin, Vadim Sokolov, and Andrei Zhdanov "Optical properties reconstruction with differentiable rendering", Proc. SPIE 12767, Optoelectronic Imaging and Multimedia Technology X, 127671L (27 November 2023); https://doi.org/10.1117/12.2688285

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available