Bayesian reconstruction of 3D human motion from single-camera video

被引：0
|
作者：
Howe, NR [1 ]
Leventon, ME [1 ]
Freeman, WT [1 ]
机构：
[1] Cornell Univ, Dept Comp Sci, Ithaca, NY 14850 USA
来源：
ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 12 | 2000年 / 12卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The three-dimensional motion of humans is underdetermined when the observation is limited to a single camera, due to the inherent 3D ambiguity of 2D video. We present a system that reconstructs the 3D motion of human subjects from single-camera video, relying on prior knowledge about human motion, learned from training data, to resolve those ambiguities. After initialization in 2D, the tracking and 3D reconstruction is automatic; we show results for several video sequences. The results show the power of treating 3D body tracking as an inference problem.
引用
收藏
页码：820 / 826
页数：7
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