Lightweight Binocular Facial Performance Capture under Uncontrolled Lighting

被引:98
作者
Valgaerts, Levi [1 ]
Wu, Chenglei [1 ,2 ]
Bruhn, Andres [3 ]
Seidel, Hans-Peter [1 ]
Theobalt, Christian [1 ]
机构
[1] MPI Informat, Saarbrucken, Germany
[2] Intel Visual Comp Inst, Saarbrucken, Germany
[3] Univ Stuttgart, D-7000 Stuttgart, Germany
来源
ACM TRANSACTIONS ON GRAPHICS | 2012年 / 31卷 / 06期
关键词
Facial Performance Capture; Scene Flow; Shading-based Refinement; Uncontrolled Lighting; 3D MOTION; SHAPE; STEREO; IMAGES; FACES; VIDEO; FLOW;
D O I
10.1145/2366145.2366206
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Recent progress in passive facial performance capture has shown impressively detailed results on highly articulated motion. However, most methods rely on complex multi-camera set-ups, controlled lighting or fiducial markers. This prevents them from being used in general environments, outdoor scenes, during live action on a film set, or by freelance animators and everyday users who want to capture their digital selves. In this paper, we therefore propose a lightweight passive facial performance capture approach that is able to reconstruct high-quality dynamic facial geometry from only a single pair of stereo cameras. Our method succeeds under uncontrolled and time-varying lighting, and also in outdoor scenes. Our approach builds upon and extends recent image-based scene flow computation, lighting estimation and shading-based refinement algorithms. It integrates them into a pipeline that is specifically tailored towards facial performance reconstruction from challenging binocular footage under uncontrolled lighting. In an experimental evaluation, the strong capabilities of our method become explicit: We achieve detailed and spatio-temporally coherent results for expressive facial motion in both indoor and outdoor scenes - even from low quality input images recorded with a hand-held consumer stereo camera. We believe that our approach is the first to capture facial performances of such high quality from a single stereo rig and we demonstrate that it brings facial performance capture out of the studio, into the wild, and within the reach of everybody.
引用
收藏
页数:11
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