Browsing by Author "Takayama, Kenshi"

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    Refinement of Hair Geometry by Strand Integration
    (The Eurographics Association and John Wiley & Sons Ltd., 2023) Maeda, Ryota; Takayama, Kenshi; Taketomi, Takafumi; Chaine, Raphaƫlle; Deng, Zhigang; Kim, Min H.
    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.