3DCMM: 3D Comprehensive Morphable Models for Accurate Head Completion

J. Zhang, Y. Luximon, Lei Zhu, Ping Li
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Abstract

3D head completion aims at recovering accurate 3D full-head geometry from 2D face images or 3D face scans. Previous 3D shape reconstruction studies primarily focused on the facial region, but ignored the scalp region. Moreover, as critical foundations in 3D head completion, powerful 3D head morphable models, however, are scarce. In this paper, we construct 3D comprehensive morphable models (3DCMM) of human faces and scalps, and develop a novel 3DCMM-based stepwise 3D full-head creation pipeline: reconstructing face regions firstly, and then completing scalp regions. Firstly, large-scale 3D heads from 2,528 identities were parameterized to construct powerful 3DCMM as our foundations. Then, a 3DCMM-based supervised converting method was presented to predict an accurate scalp region from a facial region and produce full-head geometry. Extensive experiments and comparisons demonstrated that our 3DCMM possesses better quality and descriptive power. Benefiting from this, our model-based 3D head completion method has higher accuracy than model-based fitting method.
3DCMM: 3D综合变形模型准确的头部完成
3D头部补全旨在从2D面部图像或3D面部扫描中恢复准确的3D全头部几何形状。以往的三维形状重建研究主要集中在面部区域,而忽略了头皮区域。此外,作为3D头部完成的关键基础,功能强大的3D头部变形模型却很少。本文构建了人脸和头皮的三维综合变形模型(3DCMM),并开发了一种新的基于3DCMM的三维全头创建流水线:先重建人脸区域,再完成头皮区域。首先,对2,528个身份的大尺度三维头颅进行参数化,构建强大的三维头颅模型作为基础;然后,提出了一种基于3dcmm的监督转换方法,从面部区域预测准确的头皮区域,并生成完整的头部几何形状。大量的实验和比较表明,我们的3DCMM具有更好的质量和描述能力。因此,基于模型的三维头部补全方法比基于模型的拟合方法具有更高的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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