Title :
Multi-view hair capture using orientation fields
Author :
Luo, Linjie ; Li, Hao ; Paris, Sylvain ; Weise, Thibaut ; Pauly, Mark ; Rusinkiewicz, Szymon
Abstract :
Reconstructing realistic 3D hair geometry is challenging due to omnipresent occlusions, complex discontinuities and specular appearance. To address these challenges, we propose a multi-view hair reconstruction algorithm based on orientation fields with structure-aware aggregation. Our key insight is that while hair´s color appearance is view-dependent, the response to oriented filters that captures the local hair orientation is more stable. We apply the structure-aware aggregation to the MRF matching energy to enforce the structural continuities implied from the local hair orientations. Multiple depth maps from the MRF optimization are then fused into a globally consistent hair geometry with a template refinement procedure. Compared to the state-of-the-art color-based methods, our method faithfully reconstructs detailed hair structures. We demonstrate the results for a number of hair styles, ranging from straight to curly, and show that our framework is suitable for capturing hair in motion.
Keywords :
geometry; image colour analysis; image matching; image reconstruction; MRF matching energy; MRF optimization; color-based methods; complex discontinuities; hair color appearance; hair styles; local hair orientation; multiple depth maps; multiview hair capture; multiview hair reconstruction algorithm; omnipresent occlusions; orientation fields; realistic 3D hair geometry reconstruction; specular appearance; structure-aware aggregation; template refinement procedure; Cameras; Geometry; Hair; Image reconstruction; Standards; Stereo vision; Surface reconstruction;
Conference_Titel :
Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on
Conference_Location :
Providence, RI
Print_ISBN :
978-1-4673-1226-4
Electronic_ISBN :
1063-6919
DOI :
10.1109/CVPR.2012.6247838