用于性能捕获的头戴式光度立体声

Andrew Jones, Graham Fyffe, Xueming Yu, Alex Ma, Jay Busch, M. Bolas, P. Debevec
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引用次数: 19

摘要

头戴式摄像机是一种越来越重要的工具,用于捕捉面部表演来驱动虚拟角色。它们提供了一个固定的、无遮挡的面部视图,对于观察动作捕捉点或作为视频分析的输入很有用。然而,用这些系统捕获的2D图像通常受到环境光的影响,并且通常无法记录面部执行时微妙的3D形状变化。我们已经开发了一个系统,它可以增强一个头戴式摄像头与基于led的光度立体。该系统允许在不受环境光影响的情况下观察人脸,并生成逐像素的表面法线,以便在3D中动态记录性能。由此产生的数据可以用于面部重新照明,或者作为驱动动画面部的机器学习算法的更好输入。
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Head-Mounted Photometric Stereo for Performance Capture
Head-mounted cameras are an increasingly important tool for capturing facial performances to drive virtual characters. They provide a fixed, unoccluded view of the face, useful for observing motion capture dots or as input to video analysis. However, the 2D imagery captured with these systems is typically affected by ambient light and generally fails to record subtle 3D shape changes as the face performs. We have developed a system that augments a head-mounted camera with LED-based photometric stereo. The system allows observation of the face independent of the ambient light and generates per-pixel surface normals so that the performance is recorded dynamically in 3D. The resulting data can be used for facial relighting or as better input to machine learning algorithms for driving an animated face.
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