Interactive Appearance Prediction for Cloudy Beverages

A growing trend in computer vision is the use of synthetic images for the evaluation of computer vision algorithms such as 3D pose estimation. This is partly due to the availability of high-quality render engines, which provide highly realistic synthetic images. However, the realism of the rendered images, and thus the reliability of the evaluations, strongly depends on how accurately the scenes are modeled and it requires considerable time and knowledge to do the modeling manually. Automating the modeling process is therefore crucial for making the rendering of photo-realistic synthetic images accessible to the wider robotics community.We present a method for automatically modeling object and light properties for rigid, opaque plastic objects commonly found in industry. Our method relies on recordings of the environment captured with a consumer 360 • camera to model the light, and on analysis-by-synthesis to estimate the optical properties of the objects. We show that the synthetic images rendered based on our automatic modeling method can be used to predict the overall performance of a monocular 3D pose estimation algorithm.

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Rapid Estimation of Optical Properties for Simulation-Based Evaluation of Pose Estimation Performance

Iversen

Wilm

Kraft

2019

2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Rendering Discrete Participating Media with Geometrical Optics Approximation

Guo¹,

Hu²,

Chen³

et al. 2021

Preprint

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We consider the scattering of light in participating media composed of sparsely and randomly distributed discrete particles. The particle size is expected to range from the scale of the wavelength to the scale several orders of magnitude greater than the wavelength, and the appearance shows distinct graininess as opposed to the smooth appearance of continuous media. One fundamental issue in physically-based synthesizing this appearance is to determine necessary optical properties in every local region. Since these optical properties vary spatially, we resort to geometrical optics approximation (GOA), a highly efficient alternative to rigorous Lorenz-Mie theory, to quantitatively represent the scattering of a single particle. This enables us to quickly compute bulk optical properties according to any particle size distribution. Then, we propose a practical Monte Carlo rendering solution to solve the transfer of energy in discrete participating media. Results show that for the first time our proposed framework can simulate a wide range of discrete participating media with different levels of graininess and converges to continuous media as the particle concentration increases.

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Interactive Appearance Prediction for Cloudy Beverages

Cited by 2 publications

References 12 publications

Rapid Estimation of Optical Properties for Simulation-Based Evaluation of Pose Estimation Performance

Rapid Estimation of Optical Properties for Simulation-Based Evaluation of Pose Estimation Performance

Rendering Discrete Participating Media with Geometrical Optics Approximation

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