Image-based Fitting of Procedural Yarn Models

Saalfeld, Alina; Reibold, Florian; Dachsbacher, Carsten

Image-based Fitting of Procedural Yarn Models

Files

019-022.pdf (1.27 MB)

Date

2018

Authors

Saalfeld, Alina
Reibold, Florian
Dachsbacher, Carsten

Publisher

The Eurographics Association

Abstract

While common in real life, rendering fiber and cloth accurately is challenging. Recent fiber-based, procedural rendering approaches proved to be able to capture a great amount of details of real yarn. However, the current automatic method of fitting the model parameters is expensive and inaccessible as it relies on micro CT scans of the reference yarn. The alternative is to have an artist fit the parameters by hand, which is impractical because of the large number of parameters. We present a proof-of-concept for a purely image-based approach to fit the parameters of a procedural yarn model. Using gradient descent and pixel-based loss functions, we are able to extract a subset of the model parameters from rendered images with known parameters. The appearance of the fitted models is nearly indistinguishable from the reference images.

        @inproceedings{10.2312:mam.20181194
,
booktitle = {Workshop on Material Appearance Modeling
},
editor = {Reinhard Klein and Holly Rushmeier
},
title = {{Image-based Fitting of Procedural Yarn Models
}},
author = {Saalfeld, Alina and 
Reibold, Florian and 
Dachsbacher, Carsten
},
year = {2018
},
publisher = {The Eurographics Association
},
ISSN = {2309-5059
},
ISBN = {978-3-03868-055-0
},
DOI = {10.2312/mam.20181194
}
}