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Human face structure estimation from multiple images using the 2D affine space

机译:使用2D仿射空间的多个图像的人脸结构估计

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We present an algorithm to estimate the human face structure. The input to the algorithm is not limited to an image sequence of a human head under rigid motion. It can be snapshots of the human face taken by the same or different cameras, over different periods of time. Since the depth variation of the human face is not very large, we use the affine camera projection model. Under this assumption, it can be shown that the set of 2D images produced by a 3D point feature of a rigid object can be optimally represented by two lines in the affine space. Using this property, we reformulate the (human) face structure reconstruction problem in terms of the much familiar multiple baseline stereo matching problem. Apart from the face modeling aspect, we also show how we use the results for reprojecting human faces in identification tasks.
机译:我们提出了一种估计人脸结构的算法。算法的输入不限于在刚性运动下的人头的图像序列。它可以是在不同的时间内相同或不同的摄像机拍摄的人类脸部的快照。由于人脸的深度变化不是很大,因此我们使用仿射照相机投影模型。在这种假设下,可以示出通过刚性物体的3D点特征产生的一组2D图像可以通过仿射空间中的两条线最佳地表示。使用此属性,我们在熟悉的多个基线立体声匹配问题方面重构(人类)面部结构重建问题。除了面部建模方面,我们还展示了我们如何在识别任务中恢复人类面的结果。

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