Automatic Control and Computer Sciences

, Volume 53, Issue 6, pp 522–531 | Cite as

Target Tracking Based on Multi Feature Selection Fusion Compensation in Monitoring Video

  • Yingying Feng
  • Shasha ZhaoEmail author
  • Hui Liu


This thesis is mainly targeted at self-adaptation adjustment in the search region: at first, design a staging predation space self-adaptation scale strategy bat algorithm (AP-RBA), and then, use AP-RBA algorithm to establish a target tracking strategy of optimized particle filter which can effectively solve two kinds of problems: (1) particle impoverishment phenomena produced in particle filter; (2) effective tracking targets based on few particles, thus simplifying complexity of particle filter, and then, adopt the criterion weight strategy to achieve maximum a posteriori and change of criterion weight to realize effective improvement of particle distribution and promote efficiency of particle filter process.


feature selection video monitoring target tracking moving background image segmentation 



This work is supported by Anhui province outstanding young talents support program (gxyq2017157, gxyq2017159); Anhui province major teaching reform project (2016jyxm0777); Anhui natural science research project (KJ2017A838, KJ2017A837, KJ2018A0669, KJ2018A0670).


The authors declare that they have no conflicts of interest.


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Copyright information

© Allerton Press, Inc. 2019

Authors and Affiliations

  1. 1.College of Information Engineering, Fuyang Normal UniversityFuyangChina

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