Refinement of Hair Geometry by Strand Integration

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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
} }
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