Occlusion detection and object tracking using filter banks

Author(s):  
P. Anandhakumar ◽  
J. Priyadarshini ◽  
Lakshmi Rajeswari ◽  
S. Srividhya ◽  
C. K. Niveditha
2014 ◽  
Vol 610 ◽  
pp. 393-400
Author(s):  
Jie Cao ◽  
Xuan Liang

Complex background, especially when the object is similar to the background in color or the target gets blocked, can easily lead to tracking failure. Therefore, a fusion algorithm based on features confidence and similarity was proposed, it can adaptively adjust fusion strategy when occlusion occurs. And this confidence is used among occlusion detection, to overcome the problem of inaccurate occlusion determination when blocked by analogue. The experimental results show that the proposed algorithm is more robust in the case of the cover, but also has good performance under other complex scenes.


2015 ◽  
Vol 112 ◽  
pp. 146-153 ◽  
Author(s):  
Yan Chen ◽  
Yingju Shen ◽  
Xin Liu ◽  
Bineng Zhong

2021 ◽  
Vol 15 ◽  
pp. 174830262097353
Author(s):  
Xiuyan Tian ◽  
Haifang Li ◽  
Hongxia Deng

Due to complex background and volatile object shape-appearance in image, the stability and accuracy of tracking algorithm is often disturbed and reduced. So how to accurately and robustly track object in object tracking application is a challenge topic at home and abroad. Built upon the methodologies of compressive tracking and spatio-temporal context, a simple yet robust object tracking method is proposed for solving the drift and occlusion problems in paper. It combines two existing classical ideas into a single framework: adaptive weighted idea and occlusion detection mechanism. In order to weaken interference problems of object background, object area is firstly partitioned into equal-sized sub-patches and the different weight related with location information is assigned for each patch; Then, for improving its robustness, Bhattacharyya distance is adopted to find out these samples with maximum discrimination; In addition, our proposed occlusion detection mechanism is for recapturing the tracked object when occlusion occurs. Many simulation experiments show that our proposed algorithm achieves more favorable performance than these existing state-of-the-art algorithms in handing various challenging infrared videos, especially occlusion and shape deformation.


Author(s):  
Yue Yuan ◽  
Jun Chu ◽  
Lu Leng ◽  
Jun Miao ◽  
Byung-Gyu Kim

2021 ◽  
Author(s):  
Jiaying Lin ◽  
Aravindaraja Puthiyavinayagam ◽  
Shuchen Liu ◽  
Martin Kurowski ◽  
Jan-Joran Gehrt ◽  
...  

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