基于头皮层特征点的三维头发重用方法

3D hair reusable method based on scalp layer feature points

针对在三维头发模型重用过程中,三维头发贴合到不同的人头模型时可能会出现的错位或大小不匹配的问题,提出一种基于头皮层特征点的三维头发重用方法。首先,根据模型文件的数据存储结构,分离出头发模型的头皮层,并提取特征点;其次,结合二维平面图像人脸检测方法,对目标三维人头模型的发根范围进行了特征点提取;然后,根据两个模型的特征点计算出的平移量与缩放系数,对头发模型整体进行了平移与缩放操作;最后,单独对头皮层和人头模型的贴合进行处理。最终能够使三维头发适应目标人头模型,保证头发造型信息无丢失,而且头皮层与人头模型达到了紧密贴合的效果。实验结果表明,该方法能够有效地提高三维头发模型的重用性,并且不受头发模型个性部分和分布区域等限制。

Aiming at solving the misplaced and mismatch problems when 3D hair attaches different head models in the reuse process, a 3D hair reusable method based on scalp layer feature points was proposed. Firstly, according to the data storage structure of the model file, the scalp layer was isolated from the hair model and the feature points were extracted. Secondly, combined with the 2D face image detection method, feature points of the range of hair root on head cortex were extracted. Then shift and zoom coefficients were calculated by the above mentioned feature points. Finally, the fitting process of scalp layer and head model was handled individually. Eventually the 3D hair was adapted to the target head model, which could keep hair styling information without loss. The effect of a close fit between the scalp layer and the head model was achieved. The experimental results show that the proposed method can effectively improve the reusability of 3D hair model, and it is not influenced by the restrictions of the hair model personality part and the distribution area.