Refinement of Hair Geometry by Strand Integration
No Thumbnail Available
Date
2023
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association and John Wiley & Sons Ltd.
Abstract
Reconstructing 3D hair is challenging due to its complex micro-scale geometry, and is of essential importance for the efficient creation of high-fidelity virtual humans. Existing hair capture methods based on multi-view stereo tend to generate results that are noisy and inaccurate. In this study, we propose a refinement method for hair geometry by incorporating the gradient of strands into the computation of their position. We formulate a gradient integration strategy for hair strands. We evaluate the performance of our method using a synthetic multi-view dataset containing four hairstyles, and show that our refinement produces more accurate hair geometry. Furthermore, we tested our method with a real image input. Our method produces a plausible result. Our source code is publicly available at https://github.com/elerac/strand_integration.
Description
CCS Concepts: Computing methodologies -> Reconstruction; Shape modeling
@article{10.1111:cgf.14970,
journal = {Computer Graphics Forum},
title = {{Refinement of Hair Geometry by Strand Integration}},
author = {Maeda, Ryota and Takayama, Kenshi and Taketomi, Takafumi},
year = {2023},
publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/cgf.14970}
}