Distributed multi target tracking in camera networks using sigma point information filters

Author(s):  
K. A. Shiva Kumar ◽  
K. R. Ramakrishnan ◽  
G. N. Rathna
2016 ◽  
Vol 16 (13) ◽  
pp. 5481-5490 ◽  
Author(s):  
Yanming Chen ◽  
Qingjie Zhao ◽  
Zhulin An ◽  
Peng Lv ◽  
Liujun Zhao

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Yintao Wang ◽  
Junbing Li ◽  
Qi Sun

Tracking a target in a cluttered environment is a representative application of sensor networks. In this paper, we develop a distributed approach to estimate the motion states of a target using noisy measurements. Our method consists of two parts. In first phase, using the unscented sigma-point transformation techniques and information filter framework, a class of algorithms denoted as unscented information filters was developed to estimate the states of a target to be tracked. These techniques exhibit robustness and accuracy of sigma-point filters for nonlinear dynamic inference while being as easily fused as the information filters. In the second phase, we proposed a novel consensus protocol which allows each sensor node to find a consistent estimate of the value of the target. Under this protocol, the final estimate of the value of the target at each time step is iteratively updated only by fusing the neighbors’ measurements when one sensor node is out of the measurement scope of the target. Performance of the distributed unscented information filter is demonstrated and discussed on a target tracking task.


2021 ◽  
Author(s):  
Sara Casao ◽  
Abel Naya ◽  
Ana C. Murillo ◽  
Eduardo Montijano

2019 ◽  
Vol 2019 (13) ◽  
pp. 127-1-127-7
Author(s):  
Benjamin J. Foster ◽  
Dong Hye Ye ◽  
Charles A. Bouman

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