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Structure-Aware Hair Capture
ACM Transactions on Graphics (Proc. SIGGRAPH), July 2013

Linjie Luo, Hao Li, Szymon Rusinkiewicz


Abstract

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.

Citation (BibTeX)

Linjie Luo, Hao Li, and Szymon Rusinkiewicz. Structure-Aware Hair Capture. ACM Transactions on Graphics (Proc. SIGGRAPH) 32(4), July 2013.

Paper
  PDF file (13MB)

Video
  MP4 video (183MB)

Data
  ZIP file (400MB)

Other links
  Hao Li's project page