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New Algorithm for 3D Facial Model Reconstruction and Its Application in Virtual Reality

机译:3D人脸模型重构的新算法及其在虚拟现实中的应用

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摘要

3D human face model reconstruction is essential to the generation of facial animations that is widely used in the field of virtual reality (VR). The main issues of 3D facial model reconstruction based on images by vision technologies are in twofold: one is to select and match the corresponding features of face from two images with minimal interaction and the other is to generate the realistic-looking human face model. In this paper, a new algorithm for realistic-looking face reconstruction is presented based on stereo vision. Firstly, a pattern is printed and attached to a planar surface for camera calibration, and corners generation and corners matching between two images are performed by integrating modified image pyramid Lucas-Kanade (PLK) algorithm and local adjustment algorithm, and then 3D coordinates of corners are obtained by 3D reconstruction. Individual face model is generated by the deformation of general 3D model and interpolation of the features. Finally, realistic-looking human face model is obtained after texture mapping and eyes modeling. In addition, some application examples in the field of VR are given. Experimental result shows that the proposed algorithm is robust and the 3D model is photo-realistic.
机译:3D人脸模型重构对于生成在虚拟现实(VR)领域中广泛使用的面部动画至关重要。视觉技术基于图像的3D面部模型重建的主要问题有两个:一个是从两幅图像中以最小的交互选择和匹配面部的相应特征,另一个是生成逼真的人脸模型。本文提出了一种基于立体视觉的逼真的人脸重构新算法。首先,将图案打印并附着到用于相机校准的平面上,然后通过整合改进的图像金字塔Lucas-Kanade(PLK)算法和局部调整算法,然后整合角点的3D坐标,来执行角点生成和两个图像之间的角点匹配。通过3D重建获得。通过普通3D模型的变形和特征的插值来生成个人面部模型。最后,通过纹理映射和眼睛建模获得逼真的人脸模型。此外,还给出了VR领域的一些应用示例。实验结果表明,所提算法具有鲁棒性,并且3D模型具有逼真的效果。

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