Event-based feature tracking with probabilistic data association

Author(s):  
Alex Zihao Zhu ◽  
Nikolay Atanasov ◽  
Kostas Daniilidis
2013 ◽  
Vol 380-384 ◽  
pp. 1600-1604
Author(s):  
Wan Li Xu ◽  
Zhun Liu ◽  
Jun Hui Liu

[Purpos In order to improve the accuracy of target tracking and reduce losing rate of target in the multiple target tracking, a new algorithm called Extended Probabilistic Data Association (EPDA) is presented in this paper. [Metho This paper defines joint association event based on the number of target and puts forward the EPDA for target tracking. [Result Experimental results show that this algorithm has higher accuracy of target tracking than the Probabilistic Data Association algorithm and costs much less time relative to the Joint Probabilistic Data Association algorithm. [Conclusion Consequently, EPDA is an effective algorithm to balance the accuracy and the losing rate in target tracking.


Sensors ◽  
2016 ◽  
Vol 16 (12) ◽  
pp. 2180 ◽  
Author(s):  
Xiao Chen ◽  
Yaan Li ◽  
Yuxing Li ◽  
Jing Yu ◽  
Xiaohua Li

2021 ◽  
Author(s):  
Mochammad Sahal ◽  
Zaidan Adenin Said ◽  
Rusdhianto Effendi Abdul Kadir ◽  
Zulkifli Hidayat ◽  
Yusuf Bilfaqih ◽  
...  

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