Intrinsic 3D Dynamic Surface Tracking based on Dynamic Ricci Flow and Teichmüller Map.
Intrinsic 3D Dynamic Surface Tracking based on Dynamic Ricci Flow and Teichmüller Map.
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DOI：
10.1109/iccv.2017.576
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发表时间：
2017-10
期刊：
影响因子：
--
通讯作者：
Gu X
中科院分区：
文献类型：
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作者：
Yu X;Lei N;Wang Y;Gu X
三维动态曲面跟踪是一个重要的研究课题，在许多计算机视觉和医学成像应用中起着至关重要的作用。然而，对于具有大变形和强噪声的表面序列的有效配准仍然是具有挑战性的。本文提出了一种新的基于曲面Ricci流和Teichmüller映射的非刚体三维动态曲面自动跟踪方法。根据准共形Teichmüler理论，Techmüler映射最小化了最大伸缩量，因此我们的方法能够自动配准具有大变形的曲面。此外，由于采用了Delaunay三角剖分和四边形网格，使得该方法适用于质量较低的网格。在我们的工作中，通过高速三维扫描仪获取三维动态表面。我们首先在纹理空间中使用机器学习方法识别稀疏表面特征。然后给地标特征分配不同的曲率设置，并用动态Ricci流法计算曲面的黎曼度量，使得所有的曲率都集中在特征点上，而曲面在其他地方是平坦的。帧之间的配准通过Teichmüller映射来计算，该映射以最小的角度失真对齐特征点。我们将我们的新方法应用于多个具有大表情变形的3D人脸表面序列，并将它们与其他两种最先进的跟踪方法进行了比较。精度和效率的明显提高证明了该方法的有效性。
3D dynamic surface tracking is an important research problem and plays a vital role in many computer vision and medical imaging applications. However, it is still challenging to efficiently register surface sequences which has large deformations and strong noise. In this paper, we propose a novel automatic method for non-rigid 3D dynamic surface tracking with surface Ricci flow and Teichmüller map methods. According to quasi-conformal Teichmüller theory, the Techmüller map minimizes the maximal dilation so that our method is able to automatically register surfaces with large deformations. Besides, the adoption of Delaunay triangulation and quadrilateral meshes makes our method applicable to low quality meshes. In our work, the 3D dynamic surfaces are acquired by a high speed 3D scanner. We first identified sparse surface features using machine learning methods in the texture space. Then we assign landmark features with different curvature settings and the Riemannian metric of the surface is computed by the dynamic Ricci flow method, such that all the curvatures are concentrated on the feature points and the surface is flat everywhere else. The registration among frames is computed by the Teichmüller mappings, which aligns the feature points with least angle distortions. We apply our new method to multiple sequences of 3D facial surfaces with large expression deformations and compare them with two other state-of-the-art tracking methods. The effectiveness of our method is demonstrated by the clearly improved accuracy and efficiency.