PT Unknown
AU Gemma Rotger
   Francesc Moreno-Noguer
   Felipe Lumbreras
   Antonio Agudo
TI Single view facial hair 3D reconstruction
BT 9th Iberian Conference on Pattern Recognition and Image Analysis
PY 2019
BP 423
EP 436
VL 11867
DI 10.1007/978-3-030-31332-6_37
DE 3D Vision; Shape Reconstruction; Facial Hair Modeling
AB n this work, we introduce a novel energy-based framework that addresses the challenging problem of 3D reconstruction of facial hair from a single RGB image. To this end, we identify hair pixels over the image via texture analysis and then determine individual hair fibers that are modeled by means of a parametric hair model based on 3D helixes. We propose to minimize an energy composed of several terms, in order to adapt the hair parameters that better fit the image detections. The final hairs respond to the resulting fibers after a post-processing step where we encourage further realism. The resulting approach generates realistic facial hair fibers from solely an RGB image without assuming any training data nor user interaction. We provide an experimental evaluation on real-world pictures where several facial hair styles and image conditions are observed, showing consistent results and establishing a comparison with respect to competing approaches.
ER