Woven Fabric Capture with a Reflection-Transmission Photo Pair
Yingjie Tang, Zixuan Li, Milo\v{s} Ha\v{s}an, Jian Yang, and Beibei, Wang

TL;DR
This paper introduces a novel method for digitizing woven fabrics by capturing both reflection and transmission images, using a differentiable BSDF model to accurately recover fabric parameters and improve rendering fidelity.
Contribution
It presents a new two-layer fabric BSDF model incorporating multiple scattering, enabling accurate parameter recovery from simple reflection-transmission photo pairs.
Findings
Accurately matches real woven fabrics in reflection and transmission.
Enables fabric parameter estimation with a simple setup and lightweight network.
First method to achieve consistent rendering from both reflection and transmission images.
Abstract
Digitizing woven fabrics would be valuable for many applications, from digital humans to interior design. Previous work introduces a lightweight woven fabric acquisition approach by capturing a single reflection image and estimating the fabric parameters with a differentiable geometric and shading model. The renderings of the estimated fabric parameters can closely match the photo; however, the captured reflection image is insufficient to fully characterize the fabric sample reflectance. For instance, fabrics with different thicknesses might have similar reflection images but lead to significantly different transmission. We propose to recover the woven fabric parameters from two captured images: reflection and transmission. At the core of our method is a differentiable bidirectional scattering distribution function (BSDF) model, handling reflection and transmission, including single and…
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Taxonomy
TopicsIndustrial Vision Systems and Defect Detection · Textile materials and evaluations · Optical measurement and interference techniques
