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Reconstruction of Facial Shape from Freehand Multi-viewpoint Snapshots

机译:从手法式多视点快照重建面部形状

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We propose a method that can reconstruct both a 3D facial shape and camera poses from freehand multi-viewpoint snapshots. This method is based on Active Shape Model (ASM) using a facial shape database. Most ASM methods require an image in which the camera pose is known, but our method does not require this information. First, we choose an initial shape by selecting the model from the database which is most suitable to input images. Then, we improve the model by morphing it to fit the input images. Next, we estimate the camera poses using the morphed model. Finally we repeat the process, improving both the facial shape and the camera poses until the error between the input images and the computed result is minimized. Through experimentation, we show that our method reconstructs the facial shape within 3.5mm of the ground truth.
机译:我们提出了一种方法可以从徒手多视点快照来重建3D面部形状和相机姿势。该方法基于使用面部形状数据库的主动形状​​模型(ASM)。大多数ASM方法都需要其中已知相机姿势的图像,但我们的方法不需要这些信息。首先,我们通过从数据库中选择最适合输入图像的数据库来选择初始形状。然后,我们通过改善模型来改进它以适合输入图像。接下来,我们使用变形模型估计相机姿势。最后,我们重复处理,改善面部形状和相机姿势,直到输入图像和计算结果之间的误差最小化。通过实验,我们表明我们的方法在基础事实的3.5毫米中重建了面部形状。

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