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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
Article
  • 7 Downloads

Abstract

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.

Keywords:

feature selection video monitoring target tracking moving background image segmentation 

Notes

FUNDING

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).

CONFLICT OF INTEREST

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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