Structure-Aware Hair Capture

Siggraph2013论文的Structure Aware Hair Capture演示视频
从多张照片中，将头发作为易于处理的发束信息进行3D捕捉！
太厉害了这个……

Structure-Aware Hair Capture (Siggraph 2013)

Existing hair capture systems fail to produce strands that reflect the structures of real-world hairstyles.
We introduce a system that reconstructs coherent and plausible wisps aware of the underlying hair structures from a set of still images without any special lighting.
Our system first discovers locally coherent wisp structures in the reconstructed point cloud and the 3D orientation field, and then uses a novel graph data structure to reason about both the connectivity and directions of the local wisp structures in a global optimization.
The wisps are then completed and used to synthesize hair strands which are robust against occlusion and missing data and plausible for animation and simulation.
We show reconstruction results for a variety of complex hairstyles including curly, wispy, and messy hair.

机械翻译
现有的头发捕捉系统无法生成反映现实世界发型结构的发束。
我们介绍一种系统，它无需特殊照明，仅从一组静态图像中重建出与底层头发结构相协调且合理的发束。
我们的系统首先在重建的点云和3D方向场中发现局部一致的发束结构，然后使用一种新的图结构数据结构，在全局优化中同时推理局部发束结构的连通性和方向。
随后对这些发束进行补全，并用于合成对遮挡和缺失数据具有鲁棒性、且适合动画和模拟的头发发丝。
我们展示了多种复杂发型的重建结果，包括卷发、稀疏发束和凌乱头发。

论文等内容公开在这个页面上。
Structure-Aware Hair Capture – Graphics