covariance tracking
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Automatica ◽  
2022 ◽  
Vol 136 ◽  
pp. 110078
Author(s):  
Dipankar Maity ◽  
David Hartman ◽  
John S. Baras


Author(s):  
RUHAN HE ◽  
JUN MA ◽  
JIA CHEN ◽  
DENGFENG LI ◽  
QINGJUN HUANG
Keyword(s):  


2015 ◽  
Vol 9 (6) ◽  
pp. 814-820 ◽  
Author(s):  
Qiang Guo ◽  
Chengdong Wu ◽  
Yu Feng ◽  
Xiaohong Lu


2015 ◽  
Vol 7 (1) ◽  
pp. 55
Author(s):  
Ruhan He ◽  
Yongsheng Yu ◽  
Jia Chen ◽  
Min Li ◽  
Xun Yao


Author(s):  
Andrés Romero ◽  
Lionel Lacassagne ◽  
Michèle Gouiffès ◽  
Ali Hassan Zahraee


2014 ◽  
Vol 519-520 ◽  
pp. 684-688
Author(s):  
Ying Hong Xie ◽  
Cheng Dong Wu

The existing object tracking method using covariance modeling is hard to reach the desired tracking performance when the deformation of moving target and illumination changes are drastic, we proposed a object tracking algorithm based on bilateral filtering. Firstly, the algorithm deals the image to be tracked with bilateral filtering, and extracts the needed features of filtered image to construct covariance matrix as tracking model. Secondly, under log-Euclidean Riemannian metric, we construct similarity measure for object covariance matrix and model updating strategy. Extensive experiments show that the proposed method has better adaptability for object deformation and illumination changes.



2014 ◽  
Vol 74 (6) ◽  
pp. 2157-2178 ◽  
Author(s):  
Ruhan He ◽  
Bing Yang ◽  
Nong Sang ◽  
Yongsheng Yu ◽  
Geli Bai ◽  
...  


Author(s):  
Dejun Wang ◽  
Lin Li ◽  
Wei Liu ◽  
Weiping Sun ◽  
Shengsheng Yu


2012 ◽  
Vol 21 (5) ◽  
pp. 2824-2837 ◽  
Author(s):  
Yi Wu ◽  
Jian Cheng ◽  
Jinqiao Wang ◽  
Hanqing Lu ◽  
Jun Wang ◽  
...  


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