Authors:
Chao Sun
;
Zhongrui Li
and
Won-Sook Lee
Affiliation:
University of Ottawa, Canada
Keyword(s):
Hair Modeling, Kinect v2 Sensors.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Geometric Computing
;
Geometry and Modeling
;
Modeling and Algorithms
Abstract:
Most existing hair capturing methods reconstruct 3D hair models from multi-view stereo based on complex capturing systems composed of many digital cameras and light sources. In this paper, we introduce a novel hair capturing system using consumer RGB-D (Kinect sensors). Our capture system, consisting of three Kinect v2 sensors, is much simpler than previous hair capturing systems. We directly use the 3D point clouds captured by Kinect v2 sensors as the hair volume. Then we adopt a fast and robust image enhancement algorithm to adaptively improve the clarity of the hair strands geometry based on the estimated local strands orientation and frequency from the hair images captured by the Kinect colour sensors. In addition, we introduced a hair strand grow-and-connect algorithm to generate relatively complete hair strands. Furthermore, by projecting the 2D hair strands onto the 3D point clouds, we can obtain the corresponding 3D hair strands. The experimental
results indicate that our met
hod can generate plausible 3D models for long, relatively straight hair.
(More)