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Wide-baseline hair capture using strand-based refinement

Author(s): Luo, L; Zhang, C; Zhang, Z; Rusinkiewicz, Syzmon

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Abstract: We propose a novel algorithm to reconstruct the 3D geometry of human hairs in wide-baseline setups using strand-based refinement. The hair strands are first extracted in each 2D view, and projected onto the 3D visual hull for initialization. The 3D positions of these strands are then refined by optimizing an objective function that takes into account cross-view hair orientation consistency, the visual hull constraint and smoothness constraints defined at the strand, wisp and global levels. Based on the refined strands, the algorithm can reconstruct an approximate hair surface: experiments with synthetic hair models achieve an accuracy of ~3mm. We also show real-world examples to demonstrate the capability to capture full-head hair styles as well as hair in motion with as few as 8 cameras.
Publication Date: 3-Oct-2013
Electronic Publication Date: 2013
Citation: Luo, L, Zhang, C, Zhang, Z, Rusinkiewicz, S. (2013). Wide-baseline hair capture using strand-based refinement. 265 - 272. doi:10.1109/CVPR.2013.41
DOI: doi:10.1109/CVPR.2013.41
Pages: 265 - 272
Type of Material: Conference Article
Journal/Proceeding Title: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Version: Final published version. This is an open access article.

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