| 基于形变模型的多角度三维人脸实时重建 |
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| 作者姓名： | 陈国军 曹岳 杨静 裴利强 |
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| 作者单位： | 中国石油大学(华东)计算机与通信工程学院,山东青岛,266580;中国石油大学(华东)计算机与通信工程学院,山东青岛,266580;中国石油大学(华东)计算机与通信工程学院,山东青岛,266580;中国石油大学(华东)计算机与通信工程学院,山东青岛,266580 |
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| 基金项目： | 国家“863”计划主题项目子课题(2015AA016403)；虚拟现实技术与系统国家重点实验室(北京航空航天大学)开放基金(BUAA-VR-15KF-13) |
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| 摘 要： | 摘 要：采用人脸特征点调整三维形变模型的方法应用于面部三维重建，但模型形变的计 算往往会产生误差，且耗时较长。因此运用人脸二维特征点对通用三维形变模型的拟合方法进 行改进，提出了一种视频流的多角度实时三维人脸重建方法。首先利用带有三层卷积网络的 CLNF 算法识别二维特征点，并跟踪特征点位置；然后由五官特征点位置估计头部姿态，更新 模型的表情系数，其结果再作用于 PCA 形状系数，促使当前三维模型发生形变；最后采用 ISOMAP 算法提取网格纹理信息，进行纹理融合形成特定人脸模型。实验结果表明，该方法在 人脸重建过程中具有更好的实时性能，且精确度有所提高。
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| 关 键 词： | 三维形变模型 特征点提取 表情系数 PCA形状系数 纹理融合 |
Real-Time Reconstruction of Multi-Angle 3D Human Faces Based on Morphable Model |
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| Authors: | CHEN Guo-jun CAO Yue YANG Jing PEI Li-qiang |
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| Affiliation: | (College of Computer and Communication Engineering, China University of Petroleum, Qingdao Shandong 266580, China) |
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| Abstract: | Abstract: The method that uses face landmarks to adjust the 3D morphable model is widely applied in 3D face reconstruction, but the calculation of morphable model is time-consuming and often produces errors. In this paper, we improve the fitting method of general 3D morphable model using 2D landmarks of face, and propose a real-time 3D face reconstruction method with multiple angles of video frames. First of all, we recognize the location of landmarks by the CLNF algorithm with three-layer convolutional neural networks and track the landmarks. Then, the head posture is estimated from five senses of face landmarks, and the blendshape coefficients of the model is updated, which can be used to calculate the PCA shape coefficients so as to promote the deformation of the current 3D model. Finally, we employ the ISOMAP algorithm to extract the texture information of the mesh, and proceed texture fusion to form a specific face model. Experimental results demonstrate that our method has better real-time performance and accuracy in 3D face reconstruction. |
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| Keywords: | Keywords: 3D morphable model landmarks extraction blendshape coefficients PCA shape coefficients texture fusion |
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