Multi-view Tracking of Multiple Targets with Dynamic Cameras

被引:7
作者
Kroeger, Till [1 ]
Dragon, Ralf [1 ]
Van Gool, Luc [1 ]
机构
[1] Swiss Fed Inst Technol, Comp Vis Lab, Zurich, Switzerland
来源
PATTERN RECOGNITION, GCPR 2014 | 2014年 / 8753卷
关键词
PEOPLE;
D O I
10.1007/978-3-319-11752-2_54
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We propose a new tracking-by-detection algorithm for multiple targets from multiple dynamic, unlocalized and unconstrained cameras. In the past tracking has either been done with multiple static cameras, or single and stereo dynamic cameras. We register several moving cameras using a given 3D model from Structure from Motion (SfM), and initialize the tracking given the registration. The camera uncertainty estimate can be efficiently incorporated into a flow-network formulation for tracking. As this is a novel task in the tracking domain, we evaluate our method on a new challenging dataset for tracking with multiple moving cameras and show that our tracking method can effectively deal with independently moving cameras and camera registration noise.
引用
收藏
页码:653 / 665
页数:13
相关论文
共 26 条
[1]  
Andriyenko A, 2010, LECT NOTES COMPUT SC, V6311, P466, DOI 10.1007/978-3-642-15549-9_34
[2]  
[Anonymous], 2012, CVPR
[3]  
[Anonymous], 2007, ICCV
[4]  
[Anonymous], 2011, ICCV
[5]  
[Anonymous], 2012, CVPR
[6]  
[Anonymous], 2009, CVPR
[7]  
[Anonymous], 2007, CVPR
[8]  
[Anonymous], 2012, CVPR
[9]  
[Anonymous], 2011, P CVPR
[10]  
[Anonymous], 2009, CVPR