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Single Image 3D Face Reconstruction Based on Statistical Model

机译:基于统计模型的单图像3D面重建

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摘要

Single image 3D face reconstruction technology has a broad application in the life, also has a high technical difficulties. This paper proposes a single image 3D face reconstruction technology based on statistical model. The method established 3D face statistical model based on 3D face database in advance, and trained 2D facial feature points parameter model based on the 2D face database using the algorithm of SDM. when reconstruct 3D face model from single image, first we use 2D facial feature points parameter model to extract face feature points; Then, according to 3D face model, we use adaptive learning factor gradient descent method to iteratively optimize the energy function, to get statistical model parametric vector, namely got the 3D face model corresponding to the 2D face images. The results show that use the proposed method to rebuild the faces have high similarity.
机译:单张图像3D面部重建技术在生活中具有广泛的应用,也具有高的技术困难。本文提出了一种基于统计模型的单一图像3D面重建技术。该方法基于3D面部数据库的3D面统计模型预先建立了基于SDM算法的基于2D面部数据库的2D面部特征点参数模型。从单个图像重建3D面部模型时,首先我们使用2D面部特征点参数模型来提取面部特征点;然后,根据3D面部模型,我们使用自适应学习因子梯度下降方法来迭代优化能量函数,得到统计模型参数向量,即得到了与2D面部图像对应的3D面部模型。结果表明,使用所提出的方法重建面部具有高相似性。

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