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Structure from Motion and Photometric Stereo for Dense 3D Shape Recovery

机译:运动和光度立体的结构,用于密集3D形状恢复

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In this paper we present a dense 3D reconstruction pipeline from monocular video sequences using jointly Photometric Stereo (PS) and Structure from Motion (SfM) approaches. The input videos are completely uncalibrated both from the multi-view geometry and photometric stereo aspects. In particular we make use of the 3D metric information computed with SfM from a set of 2D landmarks in order to solve for the bas-relief ambiguity which is intrinsic from dense PS surface estimation. The algorithm is evaluated over the CMU Multi-Pie database which contains the images of 337 subjects viewed under different lighting conditions and showing various facial expressions.
机译:在本文中,我们提出了结合使用光度立体(PS)和运动结构(SfM)方法的单眼视频序列的密集3D重构管道。从多视图几何和光度立体方面来看,输入视频都是完全未校准的。特别是,我们利用SfM从一组2D地标中计算出的3D度量信息,以解决密集PS表面估计所固有的浅浮雕模糊性。该算法通过CMU Multi-Pie数据库进行评估,该数据库包含在不同光照条件下查看并显示各种面部表情的337名受试者的图像。

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