Shape-From-Silhouette across time part II: Applications to human modeling and markerless motion tracking

被引:82
作者
Cheung, KM
Baker, S
Kanade, T
机构
[1] Neven Vis, Santa Monica, CA 90404 USA
[2] Carnegie Mellon Univ, Inst Robot, Pittsburgh, PA 15213 USA
关键词
human kinematic modeling; markerless motion capture; articulated human tracking; 3D reconstruction; Shape-From-Silhouette; visual hull; stereo; temporal alignment;
D O I
10.1007/s11263-005-6879-4
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In Part I of this paper we developed the theory and algorithms for performing Shape-From-Silhouette (SFS) across time. In this second part, we show how our temporal SFS algorithms can be used in the applications of human modeling and markerless motion tracking. First we build a system to acquire human kinematic models consisting of precise shape (constructed using the temporal SFS algorithm for rigid objects), joint locations, and body part segmentation (estimated using the temporal SFS algorithm for articulated objects). Once the kinematic models have been built, we show how they can be used to track the motion of the person in new video sequences. This marker-less tracking algorithm is based on the Visual Hull alignment algorithm used in both temporal SFS algorithms and utilizes both geometric (silhouette) and photometric (color) information.
引用
收藏
页码:225 / 245
页数:21
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