A recursive procedural model for improving appearance of clothes with fiber-level details

Published by Issei FUJISHIRO on

Yasunari IkedaIssei Fujishiro

in Proceedings of the 5th IIEEJ International Workshop on Image Electronics and Visual Computing, 4 pages, Da Nang, Vietnam, February 28―March 3, 2017

Making realistic yarn objects, a common material for textile, without losing details is a challenging issue. Recent methods for modeling yarn can be classified into two categories: volume-based methods and fiber-based ones. Among them, one of the latest fiber-based methods attempts to reconstruct twisted fibers from CT (Computed Tomography) images to improve the details of yarn models. While this method dramatically improves the details, mainly because of the limited resolution of the CT scanner, the fluff and fuzz of the yarn still cannot be obtained. Our goal is to realize the fluff and fuzz of yarn. To that end, we developed an extension method to attach microfibers to each fiber of the yarn. The method approximates the distribution of microfibers by recursively using statistical data. In this paper, we discuss the preliminary design of the method.

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